HYBRID SOM-SVM ALGORITHM FOR REAL TIME SERIES FORECASTING

Juan Manuel Górriz Sáez, Carlos García Puntonet and E. W. Lang

In this paper we show a new on-line parametric model for time series forecasting based on Vapnik-Chervonenkis (VC) theory. Us-ing the strong connection between support vector machines (SVM) and Regularization theory (RT), we propose a regularization operator in or-der to obtain a suitable expansion of radial basis functions (RBFs) with the corresponding expressions for updating neural parameters. This op-erator seeks for the “flattest” function in a feature space, minimizing the risk functional. Finally we mention some modifications and extensions that can be applied to control neural resources and select relevant input space.

AN ADAPTIVE SLIDING-MODE FUZZY CONTROL (ASMFC) APPROACH FOR A CLASS OF NONLINEAR SYSTEMS

Jian-Hua Zhang and Johann F. Böhme

This paper uses the concept of sliding-mode control (SMC), as a special approach in nonlinear control theory, in aiding the design of a fuzzy controller. The mathematical specifics of the presented approach are given along with its performance analysis. It was concluded that the new approach with distinctive characteristics holds potential for coping with difficult control problems for a class of complex (generally nonlinear) systems.

H CONTROL THEORY ON THE INFINITE DIMENSIONAL SPACE

Chuan-Gan Hu

In this paper, the VH^\infty control theory on an infinite dimensional algebra to itself is presented. In order to establish the VH^\infty control theory, the concept and the properties of a meromorphic mapping and the theory of VH^p spaces on an infinite dimensional algebra to itself are founded.

HBP: A NOVEL TECHNIQUE FOR DYNAMIC OPTIMIZATION OF THE FEED-FORWARD NEURAL NETWORK CONFIGURATION

Allan K.Y. Wong , Wilfred W.K. Lin and Tharam S. Dillon

The novel Hessian-based pruning (HBP) technique to optimize the feed-forward (FF) neural network (NN)configuration in a dynamic manner is proposed. It is then used to optimize the extant NNC (Neural Network Controller) as the verification exercise. The NNC is designed for dynamic buffer tuning to eliminate buffer overflow at the user/server level. The HBP optimization process is also dynamic and operates as a renewal process within the service life expectancy of the target FF neural network. Every optimization renewal cycle works with the original NN configuration. In the cycle all the insignificant NN connections are marked and then skipped in the subsequent operation before the next optimization cycle starts. The marking and skipping operations together characterize the dynamic pruning nature of the HBP. The interim optimized NN configuration produced by every HBP cycle is different, as the response to the current system dynamics. The verification results with the NNC indicate that the HBP technique is indeed effective because all the interim optimized/pruned NNC versions incessantly and consistently yield the same convergence precision to the original NNC predecessor, and with a shorter control cycle time.

DECENTRALIZED ESTIMATION FOR AGC OF POWER SYSTEMS

Xue-Bo Chen, Xiaohua Li and Srdjan S. Stankovic

A decentralized state estimation method for automatic generation control (AGC) of interconnected power systems is proposed in this paper. Based on the Inclusion Principle for linear stochastic systems, the state space model of the system is decomposed as a group of pair-wise subsystem models. The overlapping decentralized estimators and fully decentralized estimators are designed for each pair subsystems in the framework of LQG control schemes. Two types of estimators are considered for the cases of full and reduced measurement sets in the framework of system closed-loop operations. Simulation results show a high quality of the AGC scheme based on dynamic controllers with the proposed state estimators.

DEVICE INTEGRATION INTO AUTOMATION SYSTEMS WITH CONFIGURABLE DEVICE HANDLER

Anton Scheibelmasser, Udo Traussnigg, Georg Schindin and Ivo Derado

One of the most important topics in the field of automation systems is the integration of sensors, actuators,measurement devices and automation subsystems. Especially automation systems like test beds in the automotive industry impose high requirements regarding flexibility and reduced setup and integration time for new devices and operating modes. The core function of any automation system is the acquisition, evaluation and control of data received by sensors and sent to actuators. Sensors and actuators can be connected directly to the automation systems. In this case they are parameterised using specific software components, which determine the characteristics of every channel. In contrast to this, smart sensors, measurement devices or complex subsystems have to be integrated by means of different physical communication lines and protocols. The challenge for the automation system is to provide an integration platform, which will offer easy and flexible way for the integration of this type of devices. On the one hand, a sophisticated interface to the automation system should trigger, synchronise and evaluate values of different devices. On the other hand, a simple user interface for device integration should facilitate the flexible and straightforward device integration procedure for the customer. Configurable Device Handler is a software layer in the automation system, which offers a best trade-off between the complex functionality of intelligent devices and their integration in a simple, fast and flexible way. Due to a straightforward integration procedure, it is possible to integrate new devices and operation modes in a minimum of time by focusing on device functions and configuring the automation system,rather than writing software for specific device subsystems. This article gives an overview of Configurable Device Handler, which was implemented in a test bed automation system. It provides an insight into the architecture of the Configurable Device Handler and shows the principles and the ideas behind it. Finally,new aspects and future developments are discussed.

AN INSTRUMENT CONTROL SYSTEM USING PREDICTIVE MODELLING

Geoffrey Holmes and Dale Fletcher

We describe a system for providing early warning of possible error to an operator in control of an instrument providing results in batches from samples, for example, chemical elements found in soil or water samples. The system has the potential to be used with any form of instrument that provides multiple results for a given sample. The idea is to train models for each measurement, using historical data. The set of trained models are then capable of making predictions on new data based on the values of the other measurements. This approach has the potential to uncover previously unknown relationships between the measurements. An example application has been constructed that highlights the difference of the actual value for a measurement from its predicted value. The operator is provided with sliders to attenuate the sensitivity of the measurement perhaps based on its importance or its known sensitivity.

AN EVOLUTIONARY ALGORITHM FOR IDENTIFICATION OF NON-STATIONARY LINEAR PLANTS WITH TIME DELAY

Janusz P. Paplinski

The identification of time delay in the linear plant is one of the important tasks. It is especially hard problem when the plant is non-stationary. New possibility in this field is opened by application of an evolutionary algorithm. The method of identification proposed in the paper is based on three classes of input signals. In the first case we can obtain and operate on the whole unit step response. In the second way we operate on a random signal of control, and in the last we have the stairs input signal. The identification without and with disturbances is considered.

HIERARCHICAL MODAL CONTROL OF A NOVEL MANIPULATOR

Clarence de Silva and Jian Zhang

This paper focuses on the development and implementation of an intelligent hierarchical controller for the vibration control of a deployable manipulator. The emphasis is on the use of knowledge-based tuning of the low-level controller so as to improve the performance of the system. To this end, first a fuzzy inference system (FIS) is developed. The FIS is then combined with a conventional modal controller to construct a hierarchical control system. Specifically, a knowledge-based fuzzy system is used to tune the parameters of the modal controller. The effectiveness of the hierarchical control system is investigated through numerical simulation studies. Examples are considered where the system experiences vibrations due to initial disturbance at the flexible revolute joint or due to maneuvers of a deployable manipulator. The results show that the knowledge-based hierarchical control system is quite effective in suppressing vibrations induced due to the above mentioned disturbances. Results suggest that performance of the modal controller could be significantly improved through knowledge-based tuning.

AN EFFECTIVE APPROACH FOR REAL-WORLD PRODUCTION PLANNING

Jesuk Ko

This paper shows an application of constraint logic-based approach to the realistic scheduling problem. Operations scheduling, often influenced by diverse and conflicting constraints, is strongly NP-hard problem of combinatorial optimization. The problem is complicated further by real scheduling environments, where a variety of constraints in response are critical aspects for the application of a solution. Constraint logic programming technique well armed with the major function of constraint handling and solving mechanisms can be effectively applied to solve real-world scheduling problems. In this study, the scheduling problem addressed, based on a dye house involving jobs associated with the coloring of different fibers, is characterized by various constraints like color precedence, dye machine allocation and time constraints. The solution procedure used takes into account a number of dye house performance measures which include on-time delivery and resource utilization. The results indicate that constraint-based scheduling is computationally efficient in schedule generation in that a solution can be found within a few seconds. Furthermore, solutions produced always minimize the mean tardiness and maximize the utilization of dyeing facilities.

NON LINEAR SPECTRAL SDP METHOD FOR BMI-CONSTRAINED PROBLEMS: APPLICATIONS TO CONTROL DESIGN

Jean-Baptiste Thevenet, Dominikus Noll and Pierre Apkarian

The purpose of this paper is to examine a nonlinear spectral semidefinite programming method to solve problems with bilinear matrix inequality (BMI) constraints. Such optimization programs arise frequently in automatic control and are difficult to solve due to the inherent non-convexity. The method we discuss here is of augmented Lagrangian type and uses a succession of unconstrained subproblems to approximate the BMI optimization program. These tangent programs are solved by a trust region strategy. The method is tested against several difficult examples in feedback control synthesis.

RESISTANCE SPOT WELDING PROCESS IDENTIFICATION AND INITIALIZATION BASED ON SELF-ORGANIZING MAPS

Heli Junno, Perttu Laurinen, Eija Haapalainen, Lauri Tuovinen, Juha Röning, Dietmar Zettel, Daniel Sampaio, Norbert Link and Michael Peschl

Resistance spot welding is used to join two or more metal objects together, and the technique is in widespread use in, for example, the automotive and electrical industries. This paper discusses both the identification of different spot welding processes and the process initialization parameters leading to high-quality welding joints. The goal is to improve the quality of welding joints. In this research, self-organizing maps (SOMs) were used, and optimal features for the training parameters were sought. According to the results, processes can be classified by specific features. When introducing new data to trained SOMs, the welding operator can visually identify similar processes. After process identification, the most similar process is retrieved and a self-organizing map is trained for this specific process. The initialization parameters leading to successful welds in that process can thus be identified, which means that the manufacturers can use them to initialize their welding machines. It is concluded that self-organizing maps can be used to identify different spot welding processes and to find the appropriate initialization parameters for welding machines.

OPTIMIZATION OF CURRENT EXCITATION FOR PERMANENT MAGNET LINEAR SYNCHRONOUS MOTORS

Christof Röhrig

The main problem in improving the tracking performance of permanent magnet linear synchronous motors is the presence of force ripple caused by mismatched current excitation. This paper presents a method to optimize the current excitation of the motors in order to generate smooth force. The optimized phase current waveforms produce minimal ohmic losses and maximize motor efficiency. The current waveforms are valid for any velocity and any desired thrust force. The proposed optimization method consist of three stages. In every stage different harmonic waves of the force ripple are reduced. A comparison of the tracking performance with optimized waveforms and with sinusoidal waveforms shows the effectiveness of the method.

PARAMETER CONVERGENCE IN ADAPTIVE FUZZY CONTROL

Domenico Bellomo, David Naso and Robert Babuska

In this paper, the convergence of parameter estimates and the interactions among the two adaptive fuzzy systems constituting an indirect adaptive fuzzy controller are studied, both analytically and by means of simulations with a second-order nonlinear system. The analytical results and the simulations, performed with various initial conditions and learning rates, highlight how the interactions affect the behavior of the adaptive control scheme with regard to the control performance in terms of a tracking error and to the accuracy and relevance of the identified fuzzy models.

TABU SEARCH STRATEGIES IN SCHEDULING PROBLEM IN FLEXIBLE MANUFACTURING SYSTEM - Considering tool switches and number of setups

Antonio Gabriel Rodrigues, Arthur Tórgo Gómez

In this paper it’s investigated the impact of the Tabu List size, neighborhood generation approach and the managing of the decision variables of the Objective Function in the quality of a Tabu Search solution to the Scheduling Problem applied to a Flexible Manufacturing System. It was used a Part Scheduling Model, which starts with qualitatively different initial solutions that yields experiments in which it’s observed the Tabu List size influence in the results quality, according to the pre-defined Objective Function variables contribution. This Model creates a schedule in a Flexible Manufacturing System, considering resident tooling concepts, production turns, Part Selection, Machine Magazine Constraints and Due-dates. Numerical results show relations among neighborhood strategies and the Tabu List size behavior considering initial solutions and contribution managing of the Objective Function variables.

BEST-ACTION PLANNING FOR REAL-TIME RESPONSE - An approach in ORICA

Tariq Ali Omar, Ana Simonet, Michel Simonet

A planner for real-time response aims at building a plan to safely guide the world to its goal state by guaranteeing response deadlines. Ideally, it should find the best possible paths for the world. To achieve this ideal behaviour, it must be provided with maximum world behaviour characteristics and be able to control the response behaviour of the system under-control to its advantage. It should also be able to reason about one path with respect to the other, based on the execution duration, the amount of resources used and the system safety. In this paper, we present the ORICA (OSIRIS1 real-time intelligent control architecture) real-time response planner, which builds plans that permit the real-time system to strive to achieve its goal in un-guaranteed environment behaviour, while still ensuring system safety. It also possesses heuristic reasoning capability for comparison of different paths when a choice of path is possible.

A STOCHASTIC OFF LINE PLANNER OF OPTIMAL DYNAMIC MOTIONS FOR ROBOTIC MANIPULATORS

Taha Chettibi, Moussa Haddad, Samir Rebai and Abd Elfetah Hentout

we propose a general and simple method that handles free (or point-to-point) motion planning problem for redundant and non-redundant serial robots. The problem consists of linking two points in the operational space,under constraints on joint torques, jerks, accelerations, velocities and positions while minimizing a cost function involving significant physical parameters such as transfer time and joint torque quadratic average. The basic idea is to dissociate the search of optimal transfer time T from that of optimal motion parameters. Inherent constraints are then easily translated to bounds on the value of T. Furthermore, a stochastic optimization method is used which not only may find a better approximation of the global optimal motion than is usually obtained via traditional techniques but that also handles more complicated problems such as those involving discontinuous friction efforts and obstacle avoidance.

DISTRIBUTED LOAD BALANCING OF DISTRICT HEATING SYSTEMS - A SMALL-SCALE EXPERIMENT

Fredrik Wernstedt and Paul Davidsson

We present results from experiments where the effects of automatic flow control at a single substation is compared to automatic cooperative concurrent flow control at multiple substations. The latter approach is made possible by equipping individual substations with some computing power and integrating them into a communications network. Software agents, whose purpose is to cooperate with other software agents (substations) and to invoke reductions, are connected to each substation. The experiments show that it is possible to automatically load balance a small district heating network using agent technology, e.g., to perform automatic peak clipping and load shifting.

DYNAMIC BOOKING POLICY FOR AIRLINE SEAT INVENTORY CONTROL

Kristine Rozite, Nicholas A. Nechval, Konstantin N. Nechval and Edgars K. Vasermanis

It is common practice for airlines to charge several different fares for a common pool of seats. This paper presents the optimization algorithms that have been used to address the problem of when to refuse booking requests for a given fare level to save the seat for a potential request at a higher fare level. Dynamic and dynamic adaptive booking policies for multiple fare classes that share the same seating pool on one leg of an airline flight, when seats are booked in a nested fashion and when lower fare classes book before higher ones, are determined. The dynamic policy of airline booking makes repetitive use of a static method over the booking period, based on the most recent demand and capacity information. It allows one to allocate seats dynamically and anticipatory over time. The dynamic adaptive policy, in addition, deals with the case when only the functional forms of the probability density functions for reservation requests for various fare classes are given. In this case actual airline demand data are used to obtain estimates of expected demand for input into the airline optimization models, where we illustrate the practical importance of invariance for eliminating nuisance (unspecified) parameters from the problem. Although the traditional use of invariance has been in a decision theoretic setting, we instead use invariance to find a transformation of the data such that the distribution of the transformed data does not involve nuisance parameters. Illustrative examples are given.

FUZZY MODEL BASED CONTROL APPLIED TO IMAGE-BASED VISUAL SERVOING

Paulo Jorge Sequeira Gonçalves, Luís Mendonça, João Sousa and João Caldas Pinto

A new approach to eye-in-hand image-based visual servoing based on fuzzy modeling and control is proposed in this paper. Fuzzy modeling is applied to obtain an inverse model of the mapping between image features velocities and joints velocities, avoiding the necessity of inverting the Jacobian. An inverse model is identified for each trajectory using measurements data of a robotic manipulator, and it is directly used as a controller. As the inversion is not exact, steady-state errors must be compensated. This paper proposes the use of a fuzzy compensator to deal with this problem. The control scheme contains an inverse fuzzy model and a fuzzy compensator, which are applied to a robotic manipulator performing visual servoing, for a given profile of image features velocities. The obtained results show the effectiveness of the proposed control scheme: the fuzzy controller can follow a point-to-point pre-defined trajectory faster (or smoother) than the classic approach.

CONFLICT RESOLUTION FOR FREE FLIGHT CONSIDERING DEGREE OF DANGER AND CONCESSION

Mustafa Suphi Erden and Kemal Leblebicioğlu

In this study a conflict resolution technique based on danger and concession considerations is presented for free flight paradigm. A danger function which assigns a danger value for the conflict situation, and a concession function which assigns a concession value for the path followed by the aircraft are constructed. The danger and concession values are input to a fuzzy decision module. This module outputs the amount of deviation from the optimal path and the conflict is solved following these deviations. The method presented here is the third method we have been studying regarding to the conflict resolution problem. Its results are presented with a comparison to our other two studies.

QUALITATIVE AND QUANTITATIVE PROBABILISTIC TEMPORAL REASONING - for Industrial Applications

Gustavo Arroyo Figueroa

Many real-world domains, such industrial diagnosis, require an adequate representation that combines uncertainty and time. Research in this field involves the development of new knowledge representation and inference mechanisms to deal with uncertainty and time. However, current temporal probabilistic models become too complex when used for real world applications. In this paper, we propose a new model, Temporal Events Bayesian Networks (TEBN), based on a natural extension of a simple Bayesian network. TEBN tries to make a balance between expressiveness and computational efficiency. Based on a temporal node definition, causal-temporal dependencies are represented by qualitative and quantitative relations, using different time intervals within each variable (multiple granularity). Qualitative knowledge about temporal relations between variables is used to facilitate the acquisition of the quantitative parameters. The inference mechanism combines qualitative and quantitative reasoning. The proposed approach is applied to a thermal power plant through a detailed case study, with promising results.

GLOBAL CONDITION MONITORING SYSTEM - Implementing MATLAB-Based Analysis Services

Henri Helanterä, Mikko Salmenperä and Hannu Koivisto

Proactive maintenance is a solution to increase the availability of the production equipment in the process industry. It involves online condition monitoring of field devices and reliably diagnosing the reason behind any abnormal behaviour, thus helping to rationalise maintenance operations. If the huge amount of information available at the different industrial sites was available for analysis, significant improvements could be made to the predicting capabilities of condition monitoring and the accuracy of fault diagnostics. The global condition monitoring system architecture described in this paper is based on distributed agent-architecture and employs data communication networks to connect the industrial sites to one or more service centres. Many successful methods used in condition monitoring and fault diagnostics are based on various computational intelligence techniques and employing these methods often requires advanced tools. MATLAB software is a de facto standard in numerical computing but integrating MATLAB as a computing server to the J2EE-based condition monitoring system is a laborious task as no all-purpose and easy-to-use methods exist. However, this paper introduces some strategies to overcome the integration problem. The most important solution presented here is inverted calling scheme. Also two other approaches are discussed: using MATLAB engine functions via C-language native methods and deployment of stand-alone MATLAB COM components. All the above strategies have their advantages and weaknesses. Implementing the inverted call requires more effort from the programmer but is standard-compliant. Exploiting engine functions and COM components is easier as some ready-made software can be employed but the emerging solutions are not pure-Java.

AN EVOLUTIONARY APPROACH TO NONLINEAR DISCRETE - TIME OPTIMAL CONTROL WITH TERMINAL CONSTRAINTS

Yechiel Crispin

The nonlinear discrete-time optimal control problem with terminal constraints is treated using a new evolutionary approach which combines a genetic search for finding the control sequence with a solution of the initial value problem for the state variables. The main advantage of the method is that it does not require to obtain the solution of the adjoint problem which usually leads to a two-point boundary value problem combined with an optimality condition for finding the control sequence. The method is verified on two problems. The first problem is the discrete velocity direction programming with the effects of gravity and thrust, with a terminal constraint on the final vertical position. The second problem is an extension of the first problem to include the effect of viscous drag. The solutions of both problems compare favorably with the results of gradient methods.

A GROUP DECISION SUPPORT SYSTEM - A description on models and modules in GDSS based on cooperative MAS

Shi-Weiren, Jiang-Daoping, Liang-Yonglin and Chen-Jing

GDSS is popular and attractive topic in decision field. It is reasonable to combine multi-Agent technology and GDSS because they are both distributed systems and support interaction in group members. We propose models to describe character of Agent and issue in GDSS, define the workflow of group-decision as cognitive, group organizing, decision-making by cooperation, feedback and adjust decision, conduce consensus decision by negotiation, knowledge management and repository evolution, and explain the process of every part.

A DISTURBANCE COMPENSATION CONTROL FOR AN ACTIVE MAGNETIC BEARING SYSTEM BY A MULTIPLE FXLMS ALGORITHM

Min Sig Kang and Joon Lyou

In this paper, a design technique is proposed for a disturbance feedforward compensation control to attenuate disturbance responses in an active magnetic bearing system, which is subject to base motion. To eliminate the sensitivity of model accuracy to disturbance responses, the proposed design technique is an experimental feedforward compensator, developed from an adaptive estimation, by means of the Multiple Filtered-x least mean square (MFXLMS) algorithm. The compensation control is applied to a 2-DOF active magnetic bearing system subject to base motion. The feasibility of the proposed technique is illustrated, and the results of an experimental demonstration are shown.

AN INTELLIGENT RECOMMENDATION SYSTEM BASED ON FUZZY LOGIC

Shi Xiaowei

An intelligent recommendation system for a plurality of users based on fuzzy logic is presented. The architecture of a multi-agent recommendation system is described. How the system simulates human intelligence to provide recommendation to users is explained. The recommendation system is based on the fuzzy user profile, fuzzy filtering and recommendation agents. The user profile is updated dynamically based on the feedback information. Fuzzy logic is used in fuzzy filtering to integrate different types of features together for a better simulation of human intelligence. Ambiguity problems can be solved successfully in this system, e.g., deducing whether a programme with both interesting features and uninteresting features is worth recommending or not.

WHEELED VEHICLES CLASSIFICATION USING RADIAL BASE FUNCTION NEURAL NETWORK - Intelligent Control Systems and Optimization

Jerzy Jackowski and Roman Wantoch-Rekowski

The paper presents the problem of using neural network for military vehicle classification on the basis of ground vibration.

A REVIEW OF ADVANCES IN ECONOMIC DISPATCH USING ARTIFICIAL NEURAL NETWORKS

Tahir Nadeem Malik

Economic Dispatch Problem (EDP) has been discussed with reference to the developments based on mathematical programming techniques in general and Artificial Neural Networks (ANN) approaches in particular. Brief survey has been included on the Economic Dispatch in mathematical programming and optimization techniques domain. A selected survey / overview on Economic Dispatch using Artificial Neural Network within the IEE/IEEE publications frame work have been presented.

A TORQUE ESTIMATION METHOD TO AID AN INTELLIGENT MANAGEMENT SYSTEM FOR OIL WELLS AUTOMATED

Alberto S. Rebouças, Flávia N. Serafim, Milena de A. Moreira, Venício R. V. Rodeiro, Amauri Oliveira and Jés J. F. Cerqueira

This article presents a contribution for an intelligent management system for oil wells called SGPA that nowadays manages about 700 oil wells using the rod pumping lift method at Bahia State, Brazil. The intelligent management system will be applied on oil wells using the gradual pumping method. In this type of oil pumping method, the torque on the rod is very importance for detection of operational problems. It will be considered that the well is driven by an induction motor. A torque estimation method on rod and some results from laboratory are presented.

AN HORIZONTAL APPROACH TO BATCH SCHEDULING - Using the Simultaneous Manufacturing philosophy

Ana Almeida, Carlos Ramos and Sílvio do Carmo Silva

This paper is concerned with Batch Scheduling in job-shop like manufacturing systems. The Horizontal Scheduling approach is used, assuming that full scheduling of a simple or complex job, based on the job routing network of operations, from the first operation to the last, is performed before another job is considered for scheduling, having in consideration existing manufacturing processors and their availability. We follow this approach because we aim at compressing job flow time to a minimum as a strategy to meeting job due dates. To further enhance this objective the idea behind Simultaneous Manufacturing through, the widespread use of batch overlapping with Job Scheduling Patterns, which proved particularly effective in reducing job throughput time, maintaining operating simplicity and requiring reduced coordination

SCALED GRADIENT DESCENT LEARNING RATE - Reinforcement learning with light-seeking robot

Kary Främling

Adaptive behaviour through machine learning is challenging in many real-world applications such as robotics. This is because learning has to be rapid enough to be performed in real time and to avoid damage to the robot. Models using linear function approximation are interesting in such tasks because they offer rapid learning and have small memory and processing requirements. Adalines are a simple model for gradient descent learning with linear function approximation. However, the performance of gradient descent learning even with a linear model greatly depends on identifying a good value for the learning rate to use. In this paper it is shown that the learning rate should be scaled as a function of the current input values. A scaled learning rate makes it possible to avoid weight oscillations without slowing down learning. The advantages of using the scaled learning rate are illustrated using a robot that learns to navigate towards a light source. This light-seeking robot performs a Reinforcement Learning task, where the robot collects training samples by exploring the environment, i.e. taking actions and learning from their result by a trial-and-error procedure.

SOLVING THE LONGEST WORD-CHAIN PROBLEM

Nobuo Inui, Yuji Shinano, Yuusuke Kounoike and Yosiyuki Kotani

This paper describes the definition of the longest SIRITORI problem as a problem of graph and the solution based on the integer problem (IP). This formulation requires large numbers of variables in proportion to the exponential order. Against this issue, we propose a solution based on the LP-based branch-and-bound method, which gradually solves the relaxation problems. This method is able to calculate the longest SIRITORI sequences for 130 thousand words dictionary within a second. In this paper, we compare the performances for the local-heuristic search and investigate the results for several conditions to explore the longest SIRITORI problem.

MODELLING THE MAN MACHINE INTERACTION - Erotetic Logic and Information Retrieval Systems

Antonio Bellacicco and Mario Vacca

The usual communication between man and machine is a one way interaction. It can be upgraded considering a two way interaction if the basic constituents of an information retrieval system are deeply modified in their principles. In this paper we redefine, in a syntactical way, some concepts of the erotetic logic to make them more easily computable and show how them can be used to solve some problems in the field of information retrieval systems. The result is the possibility to build more flexible and powerful information retrieval systems.

MULTI-AGENTS BASED REFERENCE MODEL FOR FAULT MANAGEMENT SYSTEM IN INDUSTRIAL PROCESSES

Mariela Cerrada-Lozada, Juan Cardillo, Jose Aguilar-Castro and Raúl Faneite

Nowadays, industrial necessities claims global management procedures integrating information systems in order to manage and to use the controlled-processes information and thus, to assure a good process behaviour. These aspects aim to the development of fault detection and diagnosis systems and making-decision systems. In this work, a reference model for fault management in industrial processes is proposed. This model is based on a generic framework using multi-agent systems for distributed control systems; in this sense, the fault management problem is viewed like a feedback control process and the actions are related to the making-decision in the preventive maintenance task scheduling and the running of preventive and corrective specific maintenance tasks. A particular methodology permitting the conception and analysis of the agent systems is used for the agents design. As a result, a set of models describing the general characteristics of the agents, specific tasks, communications and coordination is obtained.

FUZZY CONTROL OF FABRICS DRYING ON AN INDUCTION HEATED ROTATING CYLINDER: Experimental results

Sergio Pérez, Zulay Niño, Normand Thérien and Arthur D. Broadbent

The removal of water from materials in textile industry and pulp and paper industry requires a high-energy consumption, increasing significantly the operating costs. Nevertheless, electromagnetic induction heating is an alternative with considerable potential for the thermal treatment of materials. Specifically, heating the surface of a metallic cylinder by electromagnetic induction has opened up a range of applications for continuos heating, pre-drying and drying of fibrous web. Otherwise, these news electrotechnologies with industrial applications have to be used under controlled operational conditions. The past few years witnessed a rapid growth in the use of fuzzy logic controllers for the control of processes, which are complex and ill defined. These control systems are inspired by the approximate reasoning capabilities of the process operator. The purpose of this paper is to improve and apply an digital control structure on the basis of fuzzy logic technique for the textile drying using a rotational cylinder heated by electromagnetic induction, manipulating the power supply to the inductors to control the exit humidity of the web. The proposed fuzzy logic controller was tested experimentally in a dryer pilot-scale plant and the results show the capability of the controller to reach the set point initially fixed at 20 g water/100 g dry fabric. Once reached the set point, continuing the trial, steps changes of the web-cylinder contact surface and the set point were done and the results shows the stability of the proposed fuzzy logic controller in both perturbations.

GENETIC ALGORITHMS APPLIED TO THE OPTIMIZATION OF GASIFICATION FOR A GIVEN FUEL

Miguel Caldas, Luisa G. Caldas and Viriato Semião

Gasification is a well-known technology that allows for a combustible gas to be obtained from a carbonaceous fuel by a partial oxidation process (POX). The resulting gas (synthesis gas or syngas) can be used either as a fuel or as a feedstock for chemical production. Recently, gasification has also received a great deal of attention concerning power production possibilities through IGCC process (Integrated Gasification Combined Cycle), which is currently the most environmentally friendly and efficient method for the production of electricity. Gasification allows for low grade fuels, or dirty fuels, to be used in an environmental acceptable way. Amongst these fuels are wastes from the petrochemical and other industries, which vary in composition shipment to shipment and from lot to lot. If operating conditions are kept constant this could result in lose of efficiency. This paper presents an application of Genetic Algorithms to optimise the operating parameters of a gasifier processing a given fuel. Two different objective functions are used: one to be used if hydrogen production if the main goal of gasification; other to be used when power/heat production is the process’s aim. The optimization method developed could be used for on-line adjustment of the gasification operating parameters for each fuel lot, or shipment, thus improving overall performance of the industrial process.

MODEL REFERENCE CONTROL IN INVENTORY AND SUPPLY CHAIN MANAGEMENT - The implementation of a more suitable cost function

Heikki Rasku, Juuso Rantala and Hannu Koivisto

A method of model reference control is investigated in this study in order to present a more suitable method of controlling an inventory or a supply chain. The problem of difficult determining of the cost of change made in the control in supply chain related systems is studied and a solution presented. Both model predictive controller and a model reference controller are implemented in order to simulate results. Advantages of model reference control in supply chain related control are presented. Also a new way of implementing supply chain simulators is presented and used in the simulations.

FIPA-OS AGENTS APPLIED TO PROCESS SCHEDULING IN REALTIME MONITORING

Angel Gómez, Diego Cantorna, Carlos Dafonte and Bernardino Arcay

This work presents a mechanism for the management of network tasks, based on the technology of Intelligent Agents applied to a project of Telemedicine in Intensive Care Units (ICUs).The telemedicine system provides the real time acquisition and analysis of physiological data of patients, the graphical visualisation of these data and their transmission to a central system charged with the collection and control of all the information concerning the patient, including knowledge based systems for medical reasoning. The system tasks are managed through the use of intelligent agents, implemented according to the FIPA standard. Each of the agents disposes of a knowledge-based system for its decision-making.

AGENTS COORDINATION IN FLAT HIERARCHICAL SOCIETY-ORIENTED SYSTEMS

Mihaela R. Cistelecan

The paper aims to propose a framework that make possible to engineer a coherent society-oriented system. For this purpose the paper investigates the opportunity of importing the concept of sliding-mode control from systems theory into the society-oriented systems. The agent is modeled as a polynomial system. Differential algebra is used as an aggregation tool for different concepts.

DATA SECURITY CONSIDERATIONS IN MODERN AUTOMATION NETWORKS

Mikko Salmenperä and Jari Seppälä

The automation manufacturing business has reached its turning point and manufacturers are forced to create new business areas. Their expertise about field devices will be the source for future growth of automation industry. This includes monitoring, maintenance, data analysis and process tuning which all require good remoting capabilities in order to be successfully and cost efficiently applied as a service for production plants. This trend builds new challenges for automation services support systems. They are forced to adapt into global business model where customers utilise network connections from old modem lines into modern mobile communication networks. "Information is power" therefore securing production and other process related information systems in modern automation networks is becoming a necessity. The resent headlines have proved that automation systems are becoming more vulnerable with the inclusion of standard office and Internet technologies into the automation networks. The only way to meet the security challenges in a global scale is to build the the connectivity using secure-by-desing methodology.

OPTIMAL DESIGN OF VARIABLE STRUCTURE LOAD FREQUENCY CONTROLLER WITH NONLINEARITIES USING TABU SEARCH ALGORITHM

Naji A. Al-Musabi, Hussain N. Al-Duwaish, A. Mantawy, Zakariya Al-Hamouz and Samir Al-Baiyat

Optimal design of Variable Structure Controller (VSC) applied to Load Frequency Control (LFC) is explored in this paper. The controller was designed by an optimal method utilizing Tabu Search (TS) algorithm. The proposed method has been applied to a single nonreheat LFC area. Nonlinearities in the form of Generation Rate Constraint (GRC) and governor deadband backlash were included in the LFC model. Conventional optimal design methods are not efficient in designing controllers for models with nonlinearities. The new optimal approach using Tabu search algorithm has been applied efficiently to these models and compared to other methods reported in literature. Simulation results show that an improved robust dynamic behaviour can be achieved with the new optimal design method.

HOW TO ESCAPE TRAPS USING CLONAL SELECTION ALGORITHMS

Vincenzo Cutello, Giuseppe Narzisi, Giuseppe Nicosia, Mario Pavone and Giuseppe Sorace

The paper presents an experimental study on clonal selection algorithms (CSAs) to optimize simple and complex trap functions. Have been tested several setting of the proposed immune algorithms to effectively face this no easy computational problem. The key feature to solve the trap functions, hence escape traps, is the usage of the hypermacromutation operator couple with a traditional perturbation immune operator, the inversely proportional to the fitness function values hypermutation operator or the static hypermutation. The experimental results show that the CSA we designed is very competitive with the best algorithm in literature.

TUNING THE PARAMETERS OF A CLASSIFIER FOR FAULT DIAGNOSIS - Particle Swarm Optimization vs Genetic Algorithms

Cosmin Danut Bocaniala and José Sa da Costa

This paper presents a comparison between the use of particle swarm optimization and the use of genetic algorithms for tuning the parameters of a novel fuzzy classifier. In previous work on the classifier, the large amount of time needed by genetic algorithms has been significantly diminished by using an optimized initial population. Even with this improvement, the time spent on tuning the parameters is still very large. The present comparison suggests that using particle swarm optimization may improve considerably the time needed for tuning the parameters. In this way, the fuzzy classifier becomes suitable for real world application. The result is validated by application to a fault diagnosis benchmark.

ITERATIVE LINEAR QUADRATIC REGULATOR DESIGN FOR NONLINEAR BIOLOGICAL MOVEMENT SYSTEMS

Weiwei Li and Emanuel Todorov

This paper presents an Iterative Linear Quadratic Regulator (ILQR) method for locally-optimal feedback control of nonlinear dynamical systems. The method is applied to a musculo-skeletal arm model with 10 state dimensions and 6 controls, and is used to compute energy-optimal reaching movements. Numerical comparisons with three existing methods demonstrate that the new method converges substantially faster and finds slightly better solutions.

A COMBINED APPROACH TO FAULT DIAGNOSIS IN DYNAMIC SYSTEMS - Application to the Three-Tank Benchmark

Luís Palma, Fernando Coito and Rui Silva

This paper presents a combined approach to fault diagnosis (FDI) in discrete-time dynamic systems. The approach integrates classical and soft computing techniques for FDI. The typical methods based on signal models, and process models for residual generation are considered: parity equations, observers and parameter estimation. The role of integration of classical and intelligent techniques is enhanced. The proposed approach is applied to a typical nonlinear feed-water system – the three-tank benchmark. The three typical fault scenarios (actuator and component faults) defined in the benchmark problem are considered in this work.

DYNAMIC ROUTING AND QUEUE MANAGEMENT VIA BUNDLE SUBGRADIENT METHODS

Almir Mutapcic, Majid Emami and Keyvan Mohajer

In this paper we propose a completely distributed dynamic network routing algorithm that simultaneously regulates queue sizes across the network. The algorithm is distributed since each node decides on its outgoing link flows based only on its own and its immediate neighbors' information. Therefore, this routing method will be adaptive and robust to changes in network topology, such as the node or link failures. This algorithm is based on the idea of bundle subgradient methods, which accelerate convergence when applied to regular non-differentiable optimization problems. In the optimal network flow framework, we show that queues can be treated as subgradient accumulations and thus bundle subgradient methods also drive average queue sizes to zero. We prove the convergence of our proposed algorithm and we state stability conditions for constant step size update rules. Algorithm is implemented using Matlab and its performance is analyzed on a test network with varying data traffic patterns.

EVOLUTIONARY APPROACH FOR DYNAMIC SCHEDULING IN MANUFACTURING

Ana Maria Madureira, Carlos Ramos and Sílvio do Carmo Silva

This paper presents a simple and general framework exploring the potential of evolutionary algorithms, which is of practical utility, embedded in a simple framework to solve difficult problems in dynamic environments. The proposed evolutionary approach is in line with reality and away from the approaches that deal with static and classic or basic Job-Shop scheduling problems. In fact, in real world, where problems are essentially of dynamic and stochastic nature, the traditional methods or algorithms are of very little use. This is the case with most algorithms for solving the so-called static scheduling problem for different setting of both single and multi-machine systems arrangements. This reality, motivated us to concentrate on tools, which could deal with such dynamic, disturbed scheduling problems, both for single and multi-machine manufacturing settings, even though, due to the complexity of these problems, optimal solutions may not be possible to find. We decided to address the problem drawing upon the potential of Genetic Algorithms to deal with such complex situations. The paper describes a scheduling system, based on Genetic Algorithms to solve the Extended Job-Shop Scheduling Problem, where the products (jobs) to be processed have due dates, release times, different assembly levels and where random perturbations may occur over time.

AN LMI OPTIMIZATION APPROACH FOR GUARANTEED COST CONTROL OF SYSTEMS WITH STATE AND INPUT DELAYS

Olga I. Kosmidou, Y. S. Boutalis and Ch. Hatzis

The robust control problem for linear systems with parameter uncertainties and time-varying delays is examined. By using an appropriate uncertainty description, a linear state feedback control law is found ensuring the closed-loop system's stability and a performance measure, in terms of the {\it guaranteed cost}. An LMI objective minimization approach allows to determine the "optimal" choice of free parameters in the uncertainty description, leading to the minimal guaranteed cost.

AN LMI-BASED GENETIC ALGORITHM FOR GUARANTEED COST CONTROL

George A. Papakostas, Olga I. Kosmidou and I. E. Antonakis

In this paper a new approach for the Guaranteed Cost Control Problem (GCCP) is presented, using two efficient tools, Linear Matrix Inequalities (LMIs) and Genetic Algorithms (GAs). A linear system with parametric uncertainty is considered for which a control law is to be found, minimizing a performance index. In a previous paper, an efficient method has been presented by using an LMI optimisation technique. A combined use of LMIs and GAs is proposed in the present approach that allows further improvement of the design procedure.

USING A DISCRETE-EVENT SYSTEM FORMALISM FOR THE MULTI-AGENT CONTROL OF MANUFACTURING SYSTEMS

Guido Maione and David Naso

In the area of Heterarchical Manufacturing Systems Modeling and Control, a relatively new paradigm is that of Multi-Agent Systems. Many efforts have been made to define the autonomous agents concurrently operating in the system and the relations between them. But few results in the current literature define a formal and unambiguous way to model a Multi-Agent System, which can be used for the real-time simulation and control of flexible manufacturing environments. To this aim, this paper extends and develops some results previously obtained by the same authors, to define a discrete event system model of the main distributed agents controlling a manufacturing system. The main mechanism of interaction between three classes of agents is presented.

FROM UML TOWARDS PETRI NETS TO SPECIFY AND VERIFY

Thouraya Bouabana-Tebibel and Mounira Belmesk

UML nowadays, has emerged as the industry standard for object-oriented modeling. However, it still lacks s a well-defined semantic base enabling it to perform formal verification and validation tasks. Our goal being to provide system designers a life cycle of software development integrating conviviality and rigor, we propose a methodology to specify, verify and validate using UML. This methodology is based on a technique which derives colored Petri nets from UML class, statechart and collaboration diagrams. The approach that we propose allows the association of the formalization of the object dynamics with the formalization of the object behavior . A case study is provided to illustrate this technique.

REAL-TIME POSITION CONTROL OF A PNEUMATIC SYSTEM USING MODEL PREDICTIVE CONTROL

Doruk Akyıldız, Umut Karahan and Can Özsoy

Studies on the precise control applications with pneumatic systems have been growing in recent years.In addition to this, due to the complexity and non-linearity of the system the expected performance will only be gained by applying modern control strategies. So the subject of this paper is identification and real-time model predictive control of a pneumatic system. In order to realise system identification, a white noise signal is sent to the plant and the displacement outputs are stored. Afterwards these data are digitally processed and the parametric single-input single-output step response model is obtained. In the previous study on this system with a PD controller, a steady-state error is observed. In order to eradicate this, a Model Predictive Control – Dynamic Matrix Control algorithm is applied. To run this, in real-time, a programme is written in Matlab - Simulink and by using the code generated by Matlab - Real-Time Workshop, the real-time position control of the system is performed.

A DECENTRALIZED ROUTE GUIDANCE ALGORITHM IN URBAN TRANSPORTATION NETWORKS

Ludovica Adacher and Gaia Nicosia

In the last decades, due to the increasing car traffic and the limited capacity of urban networks, algorithms for the traffic management and route guidance are becoming more and more important. GPS technology can be used for fleet monitoring in urban or suburban areas, from a central monitoring station (reference station) and may provide useful information concerning the movement of all vehicles. Current route guidance systems are simple from an algorithmic point of view (they compute shortest paths to the destination), but they have to deal with huge size networks. For this reason, a decentralized approach, in which each vehicle independently calculates its own route, is desirable. Naturally, to limit the congestion due the single vehicles decisions, an estimate on the different possible routes is required. Hence, we propose a decentralized algorithm in which each vehicle computes its own route on the basis of the traffic information provided by the reference station. In order to cause the vehicle to choose different paths, the algorithm is allowed to take random decisions and the reference station is informed on the routes of all vehicles, so that traffic forecast is updated.

INTELLIGENT ELECTRIC DRIVE SYSTEM - A mechatronics approach

Guy Reginald Dunlop

Drive efficiency is an important consideration in most robotic applications. A hybrid controller for permanent magnet DC motors has been developed to control the current, and hence the output torque of the motor. An H bridge is used to provide the basic PWM voltage to the motor, and the controller switches the bridge between bipolar and unipolar modes in order to minimise the switching losses within the bridge and motor, and also to minimise the electromagnetic interference. The first application presented is for a walking robot, and the second is for a dexterous robotic hand. In both cases, control is obtained from a voltage sourced inverter by means of a tight control loop that uses position readings to infer velocity so that a full DC motor model can be utilised in the control computer. For the dexterous hand, current control is by model prediction to avoid the need for direct measurement. The controller and communications are contained within a small programmable system on a chip which together with a dual H bridge driver is integrated into small circuit board that is used for distributed control within the hand.

WAVE-WP (WORLD PROCESSING) TECHNOLOGY

Peter Sapaty and Masanori Sugisaka

A new computational and control model of parallel and distributed nature has been developed. It comprises self-evolving, space-conquering automaton, high-level system navigation and coordination language, describing system problems in a spatial pattern-matching mode, and related distributed control mechanisms for management of physical, virtual, and combined worlds. The model allows us to obtain complex spatial solutions in a compact, integral, and seamless way. It can be effectively used for the creation, integration, simulation, processing, management and control of a variety of dynamic and open systems – from physical to biological, and from artificial to natural.

AIRCRAFT ELECTRICAL MONITORING & FAULT DETECTION

George Kusic

Fault detection and electrical system monitoring (management) for aircraft/spacecraft dc or 400 Hz electrical systems is presented. Real-time ‘snapshot’ data is collected from current and voltage measurement transducers on radial or loop aircraft electrical system and introduced into a State Estimator. The State Estimator ‘smoothes’ the data, detects bad transducers, and calculates the best estimate of the voltage and phase angle at busses of the network, i.e., the ‘state’ of the network. Experimental results of estimation and fault detection are presented.

CONTROL THROUGH STATE CONVERGENCE OF TELEOPERATION SYSTEMS WITH VARYING TIME DELAY

José M. Azorín, Oscar Reinoso, José M. Sabater and Rafael Aracil

Teleoperation systems that use Internet as communication channel must deal with varying time delays. In these situations, the system can become unstable due to the irregular variations of the time delay. In this paper, a control method of teleoperation systems that we presented considering constant time delays is applied to control a teleoperation system with varying time delays. The control gains obtained with a constant time delay can be used to control the teleoperation system with varying time delays because of the control method robustness. Simulation and experimental results are presented to illustrate the validity of the method.

A SHALLOW DRAFT VEHICLE FOR INTERDISCIPLINARY RESEARCH AND EDUCATION

Carl Steidley, Ray Bachnak, Wien Lohatchit, Alex Sadovsky, and Cody Ross

Water quality data collection in shallow water areas can be a challenging task. Obstacles encountered in such environments include difficulty in covering large territories and the presence of inaccessible areas due to a variety of reasons such as a soft bottom or contamination. There is also a high probability of disturbing the test area while placing the sensors. This paper describes a NASA-funded project, which has had a great deal of student involvement and is currently in the test phase, to develop a remote-controlled, shallow-draft vehicle designed as a supplemental tool for our studies of the South Texas Coastal waters. The system transmits environmental data wirelessly via a radio to a docking and control station in real-time.

ANALYSIS OF THE ARCHITECTURE AND RELIABILITY OF DATA TRANSMISSION NETWORK USED FOR RADIO BASED CAB SIGNALING SYSTEM

Wang Junfeng, Zhang Yong, Wang Huashen and Wang Xishi

The application background and basic structure of train control system based on the combination of Radio Based Cab Signaling (RBCS) and Automatic Train Protection (ATP) is introduced. The architecture of the data transmission network used for RBCS is analyzed in detail, together with the reliability of radio data transmission.

MOTION PLANNING APPROACH OF A MULTI-FINGERED ROBOT FOR CARTON FOLDING OPERATIONS

Hidetsugu Terada and Takayuki Kobayashi

The motion planning approach of a multi-fingered robot for carton folding operations has been newly developed. This approach considers the loci of the tool center point for carton flap folding operations. Also that considers the push or fixing points of the carton flap. This approach is calculated from the rotating angle of a carton flap folding and the contact position with robot finger head and carton surface, using inverse kinematics. And this approach can be applied to changes of a carton size or a folding position. In cases in which the carton flap is folded using this approach, the robot finger head touches the carton surface without slipping and moves along circular continuous path. Therefore in case of the rectangular carton box folding, each robot finger moves in each 2.5-dimensional Cartesian frame. In this report, the proposed approach is verified using a prototype robot system. This prototype system consists of two pairs of the robot fingers and rotating mechanism for carton paper. Each finger has a 3-DOF SCARA type robot and a 1-DOF linear motion system. The testing carton boxes can fold to the desired shape.

TWO APPROACHES FOR A SERVOMECHANISM CONTROL SYSTEM USING COMPUTER VISION

João Manual R. S. Tavares, Ricardo Ferreira and Francisco Freitas

In this paper a servomechanism control system based on computational vision is presented. The control Images, based in hand language, are acquired by a generic webcam and processed, in the working phase, in quasi real time. For this processing, two approaches were considered: in the first one, we used the object control moments to identify the desired order; in the second approach, we used Images control orientation histograms. In both approaches, the preset orders Images to be considered for the servomechanism vision control are acquired in the learning phase. The used servomechanism and the two approaches used for the vision control system are described and some vantages and weakness of each are indicated. An example of an image control order set, which works satisfactory, is also presented and some conclusions and future works are also addressed.

ON THE DECENTRALIZED CONTROL OF LARGE DYNAMICAL COMPLEX SYSTEM

M. Kidouche, M. Zelmat and A. Charef

This paper describes a systematic procedure to build reduced order analytical models for a design of decentralized controllers for large scale interconnected dynamical systems. The design method employs Davison techniques to affect decoupling of the interconnections into its subsystems components which is done by using the most dominant eigenvalues and the most influent inputs in each subsystem. In this way, advantage can be taken of the special structural feature of a given system to devise feasible and efficient decentralized strategies for solving large control problem which are impractical to solve by one shot centralized methods.

PREVISUALIZATION IN ROBOTICS: AN ATOMIC APPROACH

Mauno Rönkkö

In this paper, we discuss use of previsualization in robotics. In previsualization, a computer animates a highly underspecified model; thus, helping the designers to detect missing components. When applied to robotics, previsualization should reveal detailed dynamics that is not explicitly specified in the model. In particular, it should reveal interaction dynamics of the physical components. Such a requirement is non-trivial. In this paper, we investigate an atomic approach that uses emergent dynamics to reveal the interaction dynamics. The approach is based on use of atoms that obey simple, compositional interaction laws. The laws produce emergent interaction dynamics for physical components composed of atoms. As the main contribution, we shall illustrate how the atomic approach, despite its simplicity, captures compactly non-trivial settings, and reveals effortlessly intricate dynamics that are otherwise considered too laborious for modelling.

PREDICTED POLAR MAPPING FOR MOVING OBSTACLE DETECTION

Young-Joong Kim, Beom-Soo Kim and Myo-Taeg Lim

This paper presents the predicted polar mapping that is to improve the efficiency of an unexpected moving obstacle detecting system in a single vision-based robot. The polar mapping is used to simplify the segmentation of moving objects from the background and is performed with the focus of expansion (FOE) as the center. When the movement of the robot per a step becomes a bit large, then static objects or background are detected as moving objects. Thus, the velocity of the robot becomes so slow. Therefore, to enlarge the movement of the robot and to improve this system, we propose the predicted polar mapping that predicts the polar mapped image after robot moves to be admissible. In order to verify experimentally our proposed procedure, we make several comparative tests in the corridor.

FORCE RIPPLE COMPENSATOR FOR A VECTOR CONTROLLED PM LINEAR SYNCHRONOUS MOTOR

Markus Hirvonen, Heikki Handroos and Olli Pyrhönen

A dynamic model including non-idealities for a permanent magnet linear synchronous motor (PMLSM) is postulated and verified. The non-idealities acting on the physical linear motor are measured and analyzed. These experimental results are utilized in the model. The verified simulation model is used in developing a force disturbance compensator for the velocity controller of the motor. The force non-idealities, such as the cogging force, friction and load force variation, are estimated using a disturbance observer. The acceleration signal in the observer is derived through the use of a low-acceleration estimator. The significant effects of the disturbance compensator on the simulated and measured dynamics of the motor are shown.

MOTION PLANNING FOR MOBILE ROBOTS IN DYNAMIC ENVIRONMENTS

Jing Ren, Kenneth. A. McIsaac and Xishi Huang

In this paper, we present an agent-based motion planning technique for a multi-robot team in a complex dynamic environment. We define a cell-based navigation control law that can guide the robot team through the environment while avoiding collisions with both static and dynamic obstacles and other team members. To further speed up the robots' move and overcome the zigzagging phenomenon, we extend our modified Newton's method to the dynamic environment and greatly improved the system performance. To illustrate our techniques, we consider a robot team motion planning problem in a complex ``maze'' with obstacles of arbitrary shape. First, we assign potential values to a set of landmarks based on their shortest distance to the goal, and then we use a spline function to generate a potential field for the entire workspace, which is inherently free of undesired local minima. Simulation results show that robots can successfully transport materials along an optimal and collision-free path and reach the goal in a complex and dynamic maze environment. Finally we proved the team stability under all defined control laws.

LASER-BASED ADAPTIVE CRUISE CONTROL FOR INTELLIGENT VEHICLES

Miguel Ángel Sotelo, David Fernández, Eugenio Naranjo, Carlos González, Ricardo García, Teresa de Pedro and Jesús Reviejo

Vehicle and highway automation is believed to reduce the risk of accident, improve safety, increase capacity, reduce fuel consumption and enchance overall comfort and performance for drivers. One of the most important research topics in the field of Intelligent Transportation Systems (ITS) is Adaptive Cruise Control (ACC), aiming at adapting the vehicle speed to a predefined value while keeping a safe gap with regard to potential obstacles. For this purpose, a laserscanner system provides the distance between the ego vehicle and the preceding vehicle on the road. Laserscanners are able to observe the vehicle environment in order to detect, track, and classify the surrounding objects and thus providing data for active safety systems. The complete system can be understood as a Laser-based ACC controller, based on Fuzzy Logic, which assists the vehicle velocity control offering driving strategies and actuation over the throttle of a car. This controller is embedded in an automatic driving system installed in two testbed mass-produced cars operating in a real environment. The results obtained in these experiments show a good performance of the Laser-based gap controller, which is adaptable to all speeds and safe gap selections.

HYBRID CONTROL DESIGN FOR A ROBOT MANIPULATOR IN A SHIELD TUNNELING MACHINE

Jelmer Braaksma, Ben Klaassens, Robert Babuska and Cees de Keizer

In a novel shield tunneling method, the tunnel lining is produced by an extrusion process with continuous shield advance. A robotic manipulator is used to build the tunnel supporting formwork, consisting of rings of steel segments. As the shield of the tunnel-boring machine advances, concrete is continuously injected in the space between the formwork and the surrounding soil. This technology requires a fully automated manipulator, since potential human errors may jeopardize the continuity of the tunneling process. Moreover, the environment is hazardous for human operators. The manipulator has a linked structure with seven degrees of freedom and it is equipped with a head that can clamp the formwork segment. To design and test the controller, a dynamic model of the manipulator and its environment was first developed. Then, a feedback-linearizing hybrid position-force controller was designed. The design was validated through simulation in Matlab/Simulink. Virtual reality visualization was used to demonstrate the compliance properties of the controlled system.

INTEGRATING A POTENTIAL FIELD BASED PILOT INTO A MULTIAGENT NAVIGATION ARCHITECTURE FOR AUTONOMOUS ROBOTS

Manikanth Mohan, Dídac Busquets, Ramon López de Màntaras and Carles Sierra

In this paper we present a new Pilot for a Multi-Agent based control architecture for Autonomous Robots. This Pilot is based on the use of virtual potential fields and is easy to implement yet effective. The Pilot functions as an autonomous agent in a complex Multi-Agent Architecture for the control and navigation of an autonomous robot. In this architecture, various agents are responsible for different tasks, and they might have to compete and cooperate for the successful completion of a particular navigation mission. The interaction between different agents is achieved through the use of a bidding mechanism. In this respect, we also present a way to define the bid for the new pilot, so that the pilot can be integrated easily into the Multi-Agent Architecture. The pilot has been tested both on simulations and navigation experiments involving a real robot and it has given successful and encouraging results. We also deal with some problems of this pilot and ways to get around them.

VERTICAL INTEGRATION OF TTP/A FIELDBUS SYSTEMS USING WEB SERVICES

Volker Turau, Marcus Venzke, Christoph Weyer and Yesenia Vigil

This paper presents a generic technique to expose data and control of fieldbus systems to applications located at the level of operational management. To provide a high degree of interoperability between the operational level and different fieldbus systems we utilize standardized techniques such as XML, HTTP, and Web services which can be deployed independently of the platform. The proposed service is based on the interface file system for TTP/A smart transducers. The defined interface provides high level abstractions appropriate for the integration into business applications and considers the latency introduced by the internet protocols.

TRACKING OF EXTENDED CROSSING OBJECTS USING THE VITERBI ALGORITHM

Andreas Kräussling, Frank E. Schneider and Dennis Wildermuth

Tracking, which means determining the positions of the humans in the surrounding, is one of the goals in the field of mobile robots that operate in populated environments. This paper is concerned with the special problem of tracking expanded objects under such constraints. A solution in form of a Viterbi based algorithm, which can be useful for real--time systems, is presented. Thus a Maximum--a--posteriori (MAP) filtering technique is applied to perform the tracking process. The mathematical background of the algorithm is proposed. The algorithm is tested and evaluated on real and simulated data. The method uses the robots' sensors in form of a laser range finders and a motion and observation model of the objects being tracked. The special problem of the crossing of two expanded objects is considered. The mathematical background for this problem is lighted and a solution for it in form of a heuristic algorithm is proposed. This algorithm is tested on simulated and real data.

AN INTEGRATED ENVIRONMENT FOR MACHINE SYSTEM SIMULATION, REMOTE MONITORING AND FAULT DETECTION

Amos Ng, Leo De Vin, Martin Sundberg, Fredrik Oldefors, Philip Moore and Sanho Yeo

Machine service and maintenance is an intricate specialist task and machine builders often have to provide worldwide service at short notice. Machine builders would benefit enormously from the possibility to monitor and diagnose equipment operating at distant locations – both for condition-based preventive maintenance and for diagnostic purposes before flying in qualified maintenance personnel and spare parts. This paper introduces an innovative virtual engineering framework that extends the kinematics modelling and dynamics modelling capability of advanced machine simulation systems to incorporate remote monitoring and fault detection features. Specifically, it addresses the software environment that is designed to facilitate the tight integration between virtual engineering tools (machine system simulation), machine controllers (real/simulated) and model-based fault detection schemes. The underlying real-time communication framework based on the publish-subscribe model and applications interfacing techniques are also presented.

FUZZY CONTROLLER DESIGN FOR A THREE JOINT ROBOT LEG IN PROTRACTION PHASE - AN OPTIMAL BEHAVIOR INSPIRED FUZZY CONTROLLER DESIGN

Mustafa Suphi Erden and Kemal Leblebicioğlu

A fuzzy controller design is performed for a three joint robot leg in protraction phase. The aim is to develop a controller to carry the tip point to any given destination. The design is based on the inspirations derived from optimal behaviors of the leg. The optimal trajectories are obtained by using optimization methods utilizing “numerical gradient” and based on “optimal control” successively. Separate fuzzy controllers are designed for each actuator. In writing the rules each actuator is considered to be an independent agent of the leg system. The protraction motion is divided into two epochs. For each epoch different controller systems are designed to switch from one to the other in between. The crucial idea in this work is the “multi agent perspective” in designing separate fuzzy controllers for the separate joints. The results of the overall controller system are successful in carrying the tip point to any given destination, following a path resembling the optimal one.

MOCONT LOCATION MODULE: A CONTAINER LOCATION SYSTEM BASED ON DR/DGNSS INTEGRATION

Joseba Landaluze, Victoria del Río, Carlos F. Nicolás, José M. Ezkerra and Ana Martínez

The problem of identifying and adequately positioning containers in the terminal yard during handling with Reach Stackers still remains to be solved in an appropriate manner, while this is extremely important in making the identification and positioning operations automatic. A precise knowledge in the Terminal Operating System (TOS) of such data in Real Time would have considerable economic impact on the logistic treatment of operations. The MOCONT system sets out to provide a solution to this lack. In particular, the MOCONT Location Module establishes the position of the container in the yard while it is being handled by a Reach Stacker. This system is based on the integration of the Differential Global Navigation Satellite System (DGNSS) with a Dead Reckoning (DR) inertial system. This article presents the general characteristics of the MOCONT Location Module, its structure, and the structure of data fusion, besides some results obtained experimentally.

VISION-BASED TRAFFIC SIGN DETECTION FOR ASSISTED DRIVING OF ROAD VEHICLES

Miguel Ángel García, Miguel Ángel Sotelo and Ernesto Martín Gorostiza

A system for real-time traffic sign detection is described in this paper. The vision-based traffic sign detection module developed in this work is intended for assisted driving of road vehicles by handling color Images in RGB (Red, Green, Blue) format. In a first step a preattentive area of interest is determined based on the vertical projection of edge pixels. In a second step, a shape analysis is performed. In a third step, a color analysis is performed, and finally, a template is adjusted. Some results obtained on a series of real road Images are presented in order to illustrate the robustness of the detection system

CYCLOP SYSTEM: MOTION CONTROL OF MULTI-ROBOTS THROUGH A SINGLE EYE

George Tho, Douglas Tavares, Pablo Alsina and Luiz Gonçalves

We propose a way to control several robots at a glance by using visual data provided by a single vision camera. Position and orientation of the group is given by a main robot (a master) which has a very simple camera on its top. This robot also has two encoders for determining its positioning related to the origin. The other (slave) robots have no position/orientation sensors as camera/angle-sensors. Their only local sensing capabilities are light (infra-red) and bump sensors. They have a top mark that allows the master discovering their orientation and positioning through the vision software. All robots can be controled by using a control software running in a host computer, through a communication protocol also developed in this work. The robots have some software tools running inside a local processor and memory so they can perform some tasks autonomously, as obstacle avoidance. The main goal is to control all slave robots to stay inside the field of view of the master. With this behavior, the master can have control over the slaves position and can eventually send some of them to perform usefull tasks in certain places, inside its field of view.

PLAYING WITH ROBOTS AND AVATARS IN MIXED REALITY SPACES

V. Antunes, R. Wanderley, T. Tavares, P. Alsina, G. Lemos and Luiz Gonçalves

We propose a hyperpresence system designed for broad manipulation of robots and avatars in mixed reality spaces. The idea is to let human users play with robots and avatars through the internet via a mixed reality system interface. We make a mixing between hardware and software platforms for control of multi-user agents in a mixed reality environment. We introduce several new issues (or behaviors) as ``Remote Control'', ``Augmented Reality'' for robots, making robots ``Incarnating'' avatars and user humans connected through the Internet. A human user can choose which role he/she wants to play. The proposed system involves a complex implementation of heterogeneous software and hardware platforms including their integration in a real-time system working through the Internet. We performed several tests including experiments using different computer architectures and different operating systems, in order to validate the syustem.

PLATFORM-BASED TELEOPERATION CONTROL OF SYMBIOTIC HUMAN-ROBOT SYSTEM

Tao Zhang, Vuthichai Ampornaramveth, Md. Hasanuzzaman, Pattara Kiatisevi and Haruki Ueno

This paper presents a platform-based teleoperation control approach of symbiotic human-robot system. With frame-based knowledge representation, features of robots, human-robot interface and cooperative operation of symbiotic human-robot system are defined in the Software Platform of Agents and Knowledge Management (SPAK). By means of this software platform, human can communicate with robots using human-robot interface. Cooperative operation of multiple robots can be implemented by teleoperation control through wireless network. In this paper, platform-based teleoperation control of an actual symbiotic human-robot system comprised of human, humanoid robot (Robovie) and entertainment robot (AIBO) is implemented and the experimental results demonstrate its effectiveness.

A LATERAL DIRECTOR AUTOPILOT DESIGN FOR CONFLICT RESOLUTION ALGORITHMS

Mustafa Suphi Erden and Kemal Leblebicioğlu

Conflict resolution, namely avoidance of aircraft crushes, is one of the main problems to be solved in a free flight based air traffic system. In our previous work we had studied on three conflict resolution techniques, which were based on potential fields, negotiation, and the amount of the danger and concession, respectively. In the work presented here, linearized lateral aircraft dynamics is incorporated with these conflict resolution techniques. A lateral director autopilot is designed for this purpose. These three conflict resolution techniques are tested and compared on the autopilot-aircraft system. The simulation results are presented. The effects of aircraft dynamics on the generated paths are discussed.

AVOIDING VISUAL SERVOING SINGULARITIES USING A COOPERATIVE CONTROL ARCHITECTURE

Nicolas García Aracil, C. Pérez, Luis Payá, Ramon Ñeco, Jose Maria Sabater and Jose Maria Azorín

To avoid the singularities of an image-based visual control of an industrial robot (Mitsubishi PA-10), a simple and efficient control law which combines the information of two cameras in a cooperative way has been developed and tested. One of this cameras is rigidly mounted on the robot end-effector (eye-in-hand configuration) and the other one observes the robot within its workspace (eye-to-hand configuration). The system architecture proposed allows us to control the 6 dof of an industrial robot when typical problems of image-based visual control techniques are produced.

POSITION CONTROL OF AN ELECTRO-HYDRAULIC SERVOSYSTEM - A non-linear backstepping approach

Claude Kaddissi, Jean-Pierre Kenné and Maarouf Saad

This paper studies the control of an electro-hydraulic servo system using non-linear backstepping approach. Such systems are known to be highly non-linear due to many factors as leakage, friction and especially to the fluid flow expression through the servo-valve. Another fact, often neglected or avoided, is that such systems have a non-differentiable mathematical model for bi-directional applications. All these facets are pointed out in the proposed model. Therefore, such systems control should be based on non-linear strategies. Many experiments showed the failure of classic control with electro-hydraulic systems, unless operating in the neighborhood of a desired value or reference signal. The backstepping is used here to overcome all non-linear effects, but not the non-differentiable aspect. This problem is solved in this paper, by approximating the non-differentiable function by a sigmoid, so that the backstepping could always be used. In fact, simulation results show the effectiveness of the proposed approach in terms of guaranteed stability and zero tracking error.

VISUAL SERVOING TECHNIQUES FOR CONTINUOUS NAVIGATION OF A MOBILE ROBOT

Nicolas García Aracil, Oscar Reinoso, J. M. Azorín, Ezio Malis and Rafael Aracil

A new method to control the navigation of a mobile robot which is based on visual servoing techniques is presented. The new contribution of this paper could be divided in two aspects: the first one is the solution of the problem which takes place in the control law when features appear or disappear from the image plane during the navigation; and the second one is the way of providing to the control system the reference path that must be followed by the mobile robot. The visual servoing techniques used to carry out the navigation are the image-based and the intrinsic-free approaches. Both are independent of calibration errors which is very useful since it is so difficult to get a good calibration in this kind of systems. Also, the second technique allows us to control the camera in spite of the variation of its intrinsic parameters. So, it is possible to modify the zoom of the camera, for instance to get more details, and drive the camera to its reference position at the same time. An exhaustive number of experiments using virtual reality worlds to simulate a typical indoor environment have been carried out.

MAN AND WOMAN DISTINCTION USING THERMOGRAPHY

Satoshi Nishino, Igarashi Sachiyo and Atsushi Matsuda

Man and woman distinction is necessary to make security stronger and when various statistics on the visitor are taken in commercial facilities and so on. The conventional method of man and woman distinction is currently determined by using the person's appearance, the person's dress and in such cases, the way of walking, the foot pressure, the hair type.　But, these characteristics can be intentionally changed by human intervention or design. The proposed method gets a difference in the man's and woman's characteristics by taking Images of the heat distribution of the person's face by thermography. This is a man and woman distinction based on the new concept idea which this is used for. Consequently, this can be used to distinguish a man from a woman even if a man turns himself into the woman intentionally (and vice versa), because this method involves biometrics authentication.

MOBILE ROBOT LOCALIZATION BY CONSTRAINT PROPAGATION ON INTERVALS

Mélanie Delafosse, Arnaud Clérentin, Laurent Delahoche and Eric Brassart

This paper proposes to use constraint propagation on intervals to solve the mobile robot localization problem. The mobile robot is equipped with an exteroceptive sensor and dead-reckoning. These two sensors give imprecise data that are modelled by intervals. Our localization strategy is based on multi target tracking. To this aim, the data given by our two sensors are fused by constraint propagation. So, at the end of the localization process, we get a 3-D subpaving which is supposed to contain the robot’s position in a guaranteed way. The localization imprecision is naturally managed by our method.

A DSP-BASED ACTIVE CONTOUR MODEL

Juan Zapata and Ramón Ruiz

In this paper a DSP-based active contour model for tracking of the endocardium in a sequence of echocardiographic Images is presented. If a contour is available in the first frame of a sequence, the contours in the subsequent frames are segmented. Deformable active contours is a technique that combine geometry, physics and approximation theory in order to solve problems of fundamental importance to medical image analysis; such as segmentation, representation and matching of shapes, and the tracking of objects in movement. The procedure has been developed on a DSP processor using its hardware features. The results are illustrated using a sequence of four-chambers apical echocardiographic Images.

LOCATING AND CROSSING DOORS AND NARROW PASSAGES FOR A MOBILE ROBOT

Zhiyu Xiang, Vitor Santos and Jilin Liu

Behaviour based navigation for mobile robot is popular because of its clarity in hierarchy and simplicity in implementation. During the decision of the next behaviour, the environmental information provided from sensors has the priority to be taken into account. In structured indoor environment, the information was divided into three different classes with levels increasing progressively: walls, corners and passages. Besides detecting walls and corners, the paper focuses on narrow passage detecting and crossing. By detecting the Complete Points in the laser map, the two types of narrow passages are easy to find. Two immediate applications of the proposed approach emerge: localization for robots and automatic crossing of passages. The experimental results showed our success

MOBILE ROBOT LOCALIZATION USING LINEAR SYSTEM MODEL

Xu Zezhong and Liu Jilin

Localization is a fundamental problem for mobile robot autonomous navigation. EKF is an efficient tool for position estimation, but it suffers from linearization errors due to linear approximation of nonlinear system equations. In this paper we describe a position estimation method for mobile robot. Process and measurement equations are linear by appropriately constructing the state vector and system models. The position of mobile robot is estimated recursively based on optimal KF. It avoids linear approximation of nonlinear system equations and is free of linearization error. All these techniques have been implemented on our mobile robot ATRVII equipped with 2D laser rangefinder SICK.

HEXAPOD STRUCTURE EVALUATION AS WEB SERVICE

Leonardo Jelenkovic, Domagoj Jakobovic and Leo Budin

This paper describes several methods for evaluation of kinematic parameters of a Stewart platform. One of those methods is the calculation of workspace area both in numerical and graphical form. The second method allows us to analyze and estimate inherent mechanism errors that occur due to actuator errors, elastic and thermal deformations and other error sources. Furthermore, another procedure is presented which calculates certain kinematic parameters throughout the workspace area of the model and outputs them as numerical and graphical data. Finally, a forward kinematics algorithm designed for use in real-time conditions and its adaptation is presented. The described algorithms are implemented and made available as web services on the project web site.

SIMULTANEOUS LOCALIZATION AND MAPPING BASED ON MULTI-RATE FUSION OF LASER AND ENCODERS MEASUREMENTS

Leopoldo Armesto and Josep Tornero

In this paper the SLAM problem in static environments with EKF is adapted for more realistic approaches where sensors have different sampling rates. In particular, the multi-rate fusion is performed with encoders and laser rangers. Moreover, the formulation is general and can be adapted for any multi-sensor fusion application. The proposed algorithm, based on well-known techniques for feature extraction, data association and map building, is validated with some experimental results. This algorithm should been seen as a part of a complete autonomous robot navigation algorithm, also described in the paper.

SKILL ACQUISITION PROCESS OF A ROBOT-BASED AND A TRADITIONAL SPINE SURGERY

Meike Jipp, Peter Pott, Achim Wagner, Essameddin Badreddin and Werner W. Wittmann

Technological progress greatly revolutionizes medicine. Robots give the opportunity to reach greater accuracy and thus improve the medical outcome. The results of a surgical invention profoundly depend on the robot system and on the training state of the operator. Since the learning of a surgical invention can be influenced by the complexity of the system, these interconnection are investigated with psychological methods. Therefore, the skill acquisition process of a robot-based surgery is compared to a traditional spine surgery. The usage of an appropriate robot shortens the learning curve of a spine surgery due to a decreased complexity and reduces the impact of the surgeons’ psychomotor abilities on the surgery’s outcome. For the design of a surgical system, different realizations must be tested in advance regarding their cognitive workload to avoid training costs learning the operation of the system, afterwards. The methods used are not restricted to surgical robotics.

PARTIAL VIEWS MATCHING USING A METHOD BASED ON PRINCIPAL COMPONENTS

Santiago Salamanca Miño, Carlos Cerrada Somolinos, Antonio Adán Oliver and Miguel Adán Oliver

This paper presents a method to estimate the pose (position and orientation) associated to the range data of an object partial view with respect to the complete object reference system. A database storing the principal components of the different partial views of an object, which are generated virtually, is created in advance in order to make a comparison between the values computed in a real view and the stored values. It allows obtaining a first approximation to the searched pose transformation, which will be afterwards refined by applying the Iterative Closest Point (ICP) algorithm. The proposed method obtains very good pose estimations achieving very low failure rate, even in the case of the existence of occlusions. The paper describes the method and demonstrates these conclusions by presenting a set of experimental results obtained with real range data.

TOWARDS A CONCEPTUAL FRAMEWORK- BASED ARCHITECTURE FOR UNMANNED SYSTEMS

Norbert Oswald

Future unmanned aerial systems demand capabilities to perform missions automatically to the greatest possible extent. Missions like reconnaissance, surveillance, combat, or SEAD usually consist of recurring phases and contain resembling or identical portions such as autonomous flight control, sensor processing, data transmission, communication or emergency procedures. To avoid implementing many similar singular solutions, a systematic approach for the design of an unmanned avionic software architecture is needed. Current approaches focus on a coarse system design, do not integrate off-the-shelf middleware, and do not consider the needs for having on-board intelligence. This paper presents a reference software architecture to design and implement typical missions of unmanned aerial vehicles based on a Corba middleware. The architecture is composed of identical components and rests upon the peer-to-peer architectural style. It describes the internal structure of a single component with respect to autonomous requirements and provides a framework for the rapid development and implementation of new components. The framework separates functionality and middleware by hiding ORB specific statements from components. Experimental tests simulating a reconnaissance mission using various ORB implementations indicate the benefits of having an architectural design supporting multi-lingual multi-process distributed applications.

STEREO VISION SENSOR FOR 3D MEASUREMENTS - A complete solution to produce, calibrate and to verify the accuracy of the measurements results

Liviu Toma, Fangwu Shu, Werner Neddermeyer and Alimpie Ignea

Our goal was to build a stereo sensor to be used as a 3D measurement tool with direct application in car industry. The distance between the object to be measured and the stereo sensor is situated between 200 mm and 300 mm. In this paper we will present our solutions developed in order to produce, to calibrate and to verify a stereo sensor used to measure 3D coordinates with an accuracy of 0.1 mm. The measurement area is defined by a square having a side of 100 mm. We have brought two important contributions to the existing solutions. The first one is represented by the solution, we developed, to compute the coefficient of the radial distortion. The second one is represented by the image processing algorithm, developed by us, in order to minimize the errors that occur from the non-correspondence problem. The most important issues that must be solved are to define a camera model, in order to simulate as good as possible a real camera, and to be able to identify the same point with both cameras of the stereo sensor (correspondence problem), in order to reduce the measurement errors.

INTERACTIVE SOFTWARE FOR SYMBOLIC MODELING OF PHYSICAL SYSTEMS USING GRAPHS

André Laurindo Maitelli and Gilbert Azevedo da Silva

This paper presents the ModSym, a computational environment for teaching of control systems. The software implements a graphical interface for physical systems modeling using graphs. Based on the energy concept, the ModSym generalizes physical elements and dynamics variables of several physical domains as electrical, mechanical and fluid. This approach allows to represent and to connect elements of different systems in a linear graph model. Algorithms implemented in the software obtain a signal flow graph for the system linear graph and, based on it, calculate the symbolic transfer function of system using Mason’s rule.

POSITION AND ORIENTATION CONTROL OF A TWO-WHEELED DIFFERENTIALLY DRIVEN NONHOLONOMIC MOBILE ROBOT

Frederico C. Vieira, Adelardo A. D. Medeiros, Pablo J. Alsina and Antônio P. Araújo Jr.

This paper addresses the dynamic stabilization problem of a two-wheeled differentially driven nonholonomic mobile robot. The proposed strategy is based on changing the robot control variables from x, y and theta to s and theta, where s represents the robot linear displacement. Using this model, the nonholonomic constraints disappear and we show how the linear control theory can be used to design the robot controllers. This control strategy only needs the robot localization (x, y, theta), not requiring any velocity measurement or estimation. The complete derivation of the control strategy and some simulated results are presented.

AUTOMATIC ANALYSIS AND VERIFICATION OF MSC-SPECIFIED TELECOMMUNICATION SYSTEM

Lyudmila Matvyeyeva, Sergiy Kryvyy and Mariya Lopatina

Last 20 years formal methods are being used widely to specify formally, analyze, verify and test software and hardware systems, particularly, telecommunication protocols [1]. In this paper automated system is presented which specify formally and verify the telecommunication system. The automated system applies the formal modeling technique of Petri nets and is based on linear algebra methods of analysis in order to research some properties of telephone system.

PET-TYPE ROBOT COMMUNICATION SYSTEM FOR MENTAL CARE OF SINGLE-RESIDENT ELDERIES

Toshiyuki Maeda, Kazumi Yoshida, Hisao Niwa and Kazuhiro Kayashima

This paper presents a pet-type robot communication system for mental care of single-resident elderies. The robot can communicate with the people autonomously, and also it is Internet-accessible and so that allows the people to communicate with others, directly or using the communication server. The system consists of pet-type robots and the information center. The pet-type robot can treat not only as an information terminal, but as a pet, which can talk to user(s), give information of the local communities, watch over them and send some information to carers at the information center if needed. Considering necessity and sufficiency, the robot has four motors; one for both ears, one for both eyes, one for the nose, and one for the neck. Motions generated by the motors symbolize emotions of the robot, which is essential for our object. We have demonstrated and examined some features of this robot system for elderies and got some good evaluation.

VISION-BASED HAND GESTURES RECOGNITION FOR HUMAN-ROBOT INTERACTION

M. Hasanuzzaman, M. A. Bhuiyan, V. Ampornaramveth, T. Zhang, Yoshiaki Shirai and Haruki Ueno

This paper presents a vision-based hand gesture recognition system for interaction between human and robot. A real-time two hands gestures recognition system has been developed by combining three larger components analysis based on skin-color segmentation and multiple features based template-matching techniques. Gesture commands are generated and issued whenever the combinations of three skin-like regions at a particular frame match with the predefined gestures. These gesture commands are sent to robots through TCP-IP network for human-robot interaction. A method has also been proposed to detect left hand and right hand relative to face position, as well as, to detect the face and locate its position. The effectiveness of our method has been demonstrated over the interaction with a robot named ROBOVIE.

STEREOVISION APPROACH FOR OBSTACLE DETECTION ON NON-PLANAR ROADS

Sergiu Nedevschi, Radu Danescu, Dan Frentiu, Tiberiu Marita, Florin Oniga, Ciprian Pocol, Rolf Schimidt and Thorsten Graf

This paper presents a high accuracy stereovision system for obstacle detection and vehicle environment perception in various driving scenarios. The system detects obstacles of all types, even at high distance, outputting them as a list of cuboids having a position in 3D coordinates, size, speed and orientation. For increasing the robustness of the obstacle detection the non-planar road model is considered. The stereovision approach was considered to solve the road-obstacle separation problem. The vertical profile of the road is obtained by fitting a first order clothoid curve on the stereo detected 3D road surface points. The obtained vertical profile is used for a better road-obstacle separation process. By consequence the grouping of the 3D points above the road in relevant objects is enhanced, and the accuracy of their positioning in the driving environment is increased.

STRUCTURED LIGHT BASED STEREO VISION FOR COORDINATION OF MULTIPLE ROBOTS

Gui Yun Tian and Duke Gledhill

This paper reports a method of coordinating multiple robots for 3D-object handling using structured light based stereo vision. The system structure of using two robots (puma and staubli) for playing chess has been proposed. The key techniques for surface reconstruction and rejection of ‘spike’ are discussed. The feature of the active vision system for 3D object acquisition and their application for robotics and automation are introduced. Following experimental studies, conclusion and further work have been derived.

MORPHOLOGICAL CHOICE OF PLANAR MECHANISMS IN ROBOTICS

Peter Mitrouchev

In this paper a morphological confined choice for kinematic mechanisms in robotics is presented. It is based on symmetries of structures. Pairs of groups of mutually symmetrical mechanisms are detected. Thus, the number of possible configurations is confined by eliminating the symmetrical ones. Different cases of symmetries have been studied. An expression for the calculation of the number of frames and end-effectors is presented. It enables the reduction of the number of structures by avoiding those that are isomorphic. Following this, examples for applications for various kinematic structures are presented, enabling the field of research to be restricted to the possible solutions.

A FUZZY INTEGRATED APPROACH TO IMPEDANCE CONTROL OF ROBOT MANIPULATORS

Silvério J. C. Marques, Luis F. Baptista and José M. G. Sá da Costa

This paper presents an integrated fuzzy approach to recover the performance in impedance control, reducing the errors in position and force, considering uncertainties in the parameters of the manipulator dynamic model and contact surface or environment model. This integrated strategy considers a fuzzy adaptive compensator in the outer control loop that adjusts the manipulator tip position to compensate for uncertainties present in the environment. In the inner loop, a fuzzy sliding mode-based impedance controller compensates for uncertainties in the model of the manipulator, based on an inverse dynamics control law. The system error, defines the sliding surfaces of the fuzzy sliding controller as the difference between the desired and actual impedances. In order to evaluate the force/position tracking performance and to validate the proposed control structure, simulations results are presented with a three-degree-of freedom (3-DOF) PUMA robot manipulator.

TOWARDS IMPROVING ROBOTIC SOFTWARE REUSABILITY WITHOUT LOSING REAL-TIME CAPABILITIES

Frederic Pont and Roland Siegwart

We aim at improving sharability and reusability of software for autonomous mobile robots without sacrificing real-time capabilities. As a first step towards this goal, we focus on real-time Linux and we introduce the concept of a robotic hardware abstraction layer that provides for software reusability on different types of hardware and in real-time or non real-time context. We also present a preliminary implementation using RTAI Linux on the tour-guiding robot RoboX.

A REAL TIME GESTURE RECOGNITION SYSTEM FOR MOBILE ROBOTS

Vanderlei Bonato, Adriano K. Sanches, Márcio M. Fernandes, João M. P. Cardoso, Eduardo D. V. Simões and Eduardo Marques

This paper presents a vision system to be embedded in a mobile robot, both of them implemented using reconfigurable computing technology. The vision system captures gestures by means of a digital color camera, and then performs some pre-processing steps in order to use the image as input to a RAM-based neural network. The set of recognized gestures can be defined using the system on-chip training capabilities. All the above functionality has been implemented in a single FPGA chip. Experimental results have shown the system to be robust, with enough performance to meet real-time constraints (30 fps), and also high efficiency in the recognition process (true recognition rate of 99.57\%)

ROBUST SENSOR BASED NAVIGATION FOR AUTONOMOUS MOBILE ROBOT

Immanuel Ashokaraj, Antonios Tsourdos, Peter Silson and Brian White

This paper describes a new approach for mobile robot navigation using an interval analysis based adaptive mechanism for an Unscented Kalman filter. The robot is equipped with inertial sensors, encoders and ultrasonic sensors. The map used for this study is two-dimensional and it is assumed to be known a-priori. Multiple sensor fusion for robot localisation and navigation has attracted a lot of interest in recent years. An Unscented Kalman Filter (UKF) is used here to estimate the robots position using the inertial sensors and encoders. Since the UKF estimates are affected by bias, drift etc, we propose an adaptive mechanism using interval analysis with ultrasonic sensors to correct these defects in estimates. Interval analysis has been already successfully used in the past for robot localisation using time of flight sensors. But this IA algorithm has been extended to incorporate the sensor range limitation as in many real world sensors such as ultrasonic sensors. Additionally the conservativeness in the robot interval position are reduced by taking multiple sets of ultrasonic sensor measurements which are then fused using confidence weights, which depends on the area of intersection with all the other interval robot positions. One of the problems of the use of interval analysis sensor based navigation and localisation is that it can be applicable only in the presence of land marks. This problem is overcome here using additional sensors such as encoders and inertial sensors, which gives an estimate of the robot position using an Unscented Kalman filter in the absence of land marks. In the presence of land marks the complementary robot position information from the Interval analysis algorithm using ultrasonic sensors is used to estimate and bound the errors in the UKF robot position estimate.

LINEAR MODELLING AND IDENTIFICATION OF A MOBILE ROBOT WITH DIFFERENTIAL DRIVE

Patrícia N. Guerra, Pablo J. Alsina, Adelardo A. D. Medeiros and Antônio P. Araújo

This paper presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment delta l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: delta l can not directly measured. In this paper, this problem is solved using an estimate delta l based on a second order curve approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot.

MULTILEVEL DARWINIST BRAIN IN ROBOTS - Initial Implementation

Francisco Bellas and Richard J. Duro

In this paper we present a Cognitive Mechanism called MDB (Multilevel Darwinist Brain) based on Darwinist theories and its initial application to autonomous learning by robotic systems. The mechanism has been designed to permit an agent to adapt to its environment and motivations in an autonomous way. The general structure of the MDB is particularized into a two level architecture: reasoning and interaction. This structure corresponds to a generic cognitive model where world, internal and satisfaction models are used to select strategies that fulfil the motivation of the agent. The main idea behind the proposal is that all of the components of the mechanism are obtained and modified through interaction with the environment in real time by means of on line Darwinist processes, allowing for a natural learning curve. The mechanism is able to provide solutions based on experience or original solutions to new situations. The knowledge used by the agent is acquired automatically and not imposed by the designer. Here we discuss the basic operation of the mechanism and demonstrate it through a real example in which a hexapod robot is taught to walk efficiently and to reach an objective around it

REALWORLD ROBOT NAVIGATION BY TWO DIMENSIONAL EVALUATION REINFORCEMENT LEARNING

Hiroyuki Okada

The trade-off of exploration and exploitation is present for a learnig method based on the trial and error such as reinforcement learning. We have proposed a reinforcement learning algorism using reward and punishment as repulsive evaluation(2D-RL). In the algorithm, an appropriate balance between exploration and exploitation can be attained by using interest and utility. In this paper, we applied the 2D-RL to a navigation learning task of mobile robot, and the robot found a better path in real world by 2D-RL than by traditional actor-critic model.

ACTIVE SENSING STRATEGIES FOR ROBOTIC PLATFORMS, WITH AN APPLICATION IN VISION-BASED GRIPPING

Benjamin Deutsch, Frank Deinzer, Matthias Zobel and Joachim Denzler

We present a vision-based robotic system which uses a combination of several active sensing strategies to grip a free-standing small target object with an initially unknown position and orientation. The object position is determined and maintained with a probabilistic visual tracking system. The cameras on the robot contain a motorized zoom lens, allowing the focal lengths of the cameras to be adjusted during the approach. Our system uses an entropy-based approach to find the optimal zoom levels for reducing the uncertainty in the position estimation in real-time. The object can only be gripped efficiently from a few distinct directions, requiring the robot to first determine the pose of the object in a classification step, and then decide on the correct angle of approach in a grip planning step. The optimal angle is trained and selected using reinforcement learning, requiring no user-supplied knowledge about the object. The system is evaluated by comparing the experimental results to ground-truth information.

SCAN MATCHING WITHOUT ODOMETRY INFORMATION

Francesco Amigoni, Simone Gasparini and Maria Gini

We present an algorithm for merging two partial maps obtained with a laser range scanner into a single map. The most unique aspect of our algorithm is that it does not require any information on the position where the scans were collected. The algorithm operates by performing a geometric match of the two scans and returns the best fused map obtained by merging the two partial maps. The algorithm attempts to reduce the number of segments in the fused map, by replacing overlapping segments with a single segment. We present heuristics to speed up the computation, and experimental results obtained with a mobile robot in an indoor environment.

A MOBILE ROBOT MAPPING SYSTEM WITH AN INFORMATION-BASED EXPLORATION STRATEGY

Francesco Amigoni, Vincenzo Caglioti and Umberto Galtarossa

The availability of efficient mapping systems to produce accurate representations of initially unknown environments is undoubtedly one of the main requirements for autonomous mobile robots. This paper presents a mapping system that has been implemented on a mobile robot equipped with a laser range scanner. The system builds geometrical maps of the environment employing an exploration strategy that takes into account both the distance travelled and the information gathered to determining the observation positions. This strategy is based on stronger mathematical foundations than the exploration strategies proposed in literature: this is the distinctive feature of our approach and constitutes the main original contribution of this paper.

FROM PETRI NETS TO EXECUTABLE SYSTEMS: AN ENVIRONMENT FOR CODE GENERATION AND ANALYSIS

Joao Paulo Barros, Luís Gomes, Rui Pais and Rui Dias

There is an increased awareness regarding the importance of executable system's specifications, in particular, graphical specifications. Although most Petri nets variants are recognised as a versatile formalism, with an intuitive graphical specifications and a precise semantics, most Petri nets tools limit themselves to graphical editing and some type of simulation, system analysis, or both. This paper presents a new development environment based on Petri nets. This environment enables the use of \emph{ad-hoc} Petri net classes as domain specific languages and allows the net models compositions and evolution through a set of orthogonal and generic modification operations. It also generates ANSI C code (or other executable code) amenable to be implemented in general-purpose hardware platforms, without sophisticated resources available. Additionally, one major environment feature is the use of the same generated executable code, both for simulation and for analysis purposes.

ABOUT NATURE OF EMERGENT BEHAVIOR IN MICRO-SYSTEMS

Sergey Kornienko, Olga Kornienko and Paul Levi

Micro-robotic systems have very limited computational and communicating resources on board. However they have a broad spectra of tasks (surface cleaning, micro-assembling, collective perception) to be solved. One of approaches to solve these tasks by such capability-restricted systems consists in utilizing emergent properties of many interacting robots. In the presented work we consider the questions what is the emergent behavior in technical systems and how this artificial emergence differs from the natural analogue ? These points are discussed on examples of spatial and functional emergence in micro-systems.

ON THE RECONSTRUCTION PERFORMANCE OF COMPRESSED ORTHOGONAL MOMENTS

George A. Papakostas, Yiannis S. Boutalis, D. A. Karras and B. G. Mertzios

In this paper, a wavelet-based technique is applied to three moment feature vectors corresponding to three different families of orthogonal moments. The resulted compressed vectors are studied experimentally, in order to extract useful information about their behaviour to a reconstruction procedure. The reconstruction performance of these moments is identical to the amount of image information that they contain to certain moment orders. Since the moment vectors are imposed to compression at the high frequency components, a conclusion about their information redundancy can be also determined. The most efficient moment family, by means of the reconstruction error, will form feature vectors with low dimension, yet with high information content and thus will be very useful for pattern recognition applications, guarantying high recognition rates.

AUTOMATIC VISION-BASED MONITORING OF THE SPACECRAFT DOCKING APPROACH WITH THE INTERNATIONAL SPACE STATION

Andrey A. Boguslavsky, Victor V. Sazonov, Sergey M. Sokolov, Alexandr I. Smirnov and Khamzat S. Saigiraev

The software package allowing automating the visual monitoring of the spacecraft docking approach with the international space station is considered. The initial data for this complex is the video signal received from the TV-camera, mounted on board the spacecraft. The offered algorithms of this video signal processing in real time allow restoring the basic characteristics of spacecraft motion with respect to international space station. The results of experiments with the described software and real video data about docking approach of the spacecraft Progress with international space station are presented. The accuracy of the estimation of the motion characteristics and perspectives the use of the package are discussed.

A CONCEPT LEARNING BASED APPROACH TO MOTION CONTROL FOR HUMANOID ROBOTS

Kiyotake Kuwayama, Shohei Kato and Hidenori Itoh

This paper proposes a concept learning-based approach to motion control for humanoid robots. In this approach, the motion control system is implemented with "decision tree learner" for the acquisition of balancing property of itself body and movement and "depth first search technique" for the motion control based on the knowledge concerning balance and stability in the motion. Some performance results by humanoid robot HOAP-1 is reported: stable and anti-tumble motions to stand up from a chair. This paper also reports some performance for the change in the environments; stand up from a chair on slope and different in height.

DEAD RECKONING FOR MOBILE ROBOTS USING TWO OPTICAL MICE

Andrea Bonarini, Matteo Matteucci and Marcello Restelli

In this paper, we present a dead reckoning procedure to support reliable odometry on mobile robot. It is based on a pair of optical mice rigidly connected to the robot body. The main advantages are that: 1) the measurement given by the mice is not subject to slipping, since they are independent from the traction wheels, nor to crawling, since they measure displacements in any direction, 2) this localization system is independent from the kinematics of the robot, 3) it is a low-cost solution. We present the mathematical model of the sensor, its implementation, and some empirical evaluations.

A INTERPOLATION-BASED APPROACH TO MOTION GENERATION FOR HUMANOID ROBOTS

Koshiro Noritake, Shohei Kato and Hidenori Itoh

This paper proposes a static posture based motion generation system for humanoid robots. The system generates a sequence of motion from given several postures, and the motion is smooth and stable in the balance. We have produced all the motions of Tai Chi Chuan by the system. Motion generation for humanoids has been studied mainly based on the dynamics. Dynamic based method has, however, some defects: e.g., numerous parameters which can not be always prepared, expensive computational cost and no guarantee that the motions are stable in balance. We have, thus, studied less dependent-on-dynamics approach. A motion is described as a sequence of postures. Our system figure out if we need extra postures to insert for stability. This method enables humanoid robot, HOAP-1 to do Tai Chi Chuan.

AUTOLOCALIZATION USING THE CONVOLUTION OF THE EXTENDED ROBOT

Eduardo Espino, Vidal Moreno, Belen Curto and Ramiro Aguilar

In order to construct autonomous robots which they move in a indoor environment, it is necessary to solve several problems such as the autolocalization. The problem of the autolocalization in a robot mobile consists of it must find its location within an apriori known map of its surroundings using the perceived distances by its sensors and also taking into account the control signals that drive their wheels. The difficulties come from the fact that the signals of the sensors have noise, as well as the control signals and also the map could differ from the reality of the surroundings. The method which we presented joins the measures of the sensors and the signals of control in the called map of the extended robot; through of the convolution of this map and the a priori map of the environment, we can find the best matching between them, after a search into this calculated values, the location is obtained as a configuration that corresponds to the global maximum convolution. The method was implemented in an sonar-based robot, with kinematics differential. The results have validated widely our proposal.

SUPERVISION AND TELECONTROL OF A RADIO BROADCASTING SYSTEM VIA INTERNET

Joan Aranda and Eduard Sanz

In this paper a recent application is showed that uses Internet as a supervision tool and remote control of a network of radio-TV relay stations to offer a better service to future clients. The relay stations network occupies a region of about 30.000 km2. The operator of this telecommunications network counts with a SCADA system which permits to the operator monitoring and control of the whole network. With the presented application users of the network can access to real time information about relevant aspects of the emission or change some parameters at anytime and from anywhere thanks to internet. The application has been implemented on a PC equipped with Windows NT 4.0 and it has been developed using VisualStudio 6.0 tools. The aspects of access security and safe communications have been taken care specially.

REALISTIC DYNAMIC SIMULATION OF AN INDUSTRIAL ROBOT WITH JOINT FRICTION

Ronald G. K. M. Aarts, Ben J. B. Jonker and Rob R. Waiboer

This paper presents a realistic dynamic simulation of the closed-loop tip motion of a rigid-link manipulator with joint friction. The results from two simulation techniques are compared with experimental results. A six-axis industrial Stäubli robot is modelled. The LuGre friction model is used to account both for the sliding and pre-sliding regime. The manipulation task implies transferring a laser spot along a straight line with a trapezoidal velocity profile. Firstly, a non-linear finite element method is used to formulate the dynamic equations of the manipulator mechanism. In a closed-loop simulation the driving torques are generated by the control system. The computed trajectory tracking errors agree well with the experimental results. Unfortunately, the simulation is very time-consuming due to the small time step of the discrete-time controller. Secondly, a perturbation method has been applied. In this method the perturbed motion of the manipulator is modelled as a first-order perturbation of the nominal manipulator motion. Friction torques at the actuator joints are introduced at the stage of perturbed dynamics. A substantial reduction of the computer time is achieved without loss of accuracy.

CONSTRUCTION OF THE VORONOI DIAGRAM BY A TEAM OF COOPERATIVE ROBOTS

Flavio S. Mendes, Júlio S. Aude, Paulo C. V. Pinto and Eliana P.L. Aude

This paper presents a method for cooperation in the construction of Voronoi diagrams which is suitable for use in dangerous tasks performed by a team of robots. The algorithm has been implemented on a network of eight workstations using the MPI library. Two implementation approaches have been used. In the first one, no communication among the robots is required but some degree of redundancy in the work performed by the robots may result. In the second approach, a more cooperative scheme is adopted and, as a consequence, communication among the robots increases but the work performed by each one is reduced. In both approaches, the calculation time decreases almost linearly when adding robots to the team. Nevertheless, the second approach, more cooperative, has consistently produced better results. With the achieved speed-up, it is possible to use this algorithm in applications where the obstacle configuration within the robot team working area changes with time.

DYNAMIC TOOLS TO CONTROL COMPLEX SYSTEMS

Mahfoud Mabed

The idea of complex sequencing is strongly related to scheduling and real time systems. It appears when a resource has to be shared by more than one user or when a job must be handled by some concurrent entities. The originality of our research is mainly to build a dynamic link between a scheduling solution and a simulation approach based on Petri Nets (PN). This paper addresses with the modeling of an electroplating line with max plus algebra theory and Petri Nets. As a schedule representing a sequence that contains a series of jobs, we can obtain a corresponding polynomial by using Lagrange interpolation. Then, we can use these polynomials to ensure a real time connection between a schedule procedure and a Petri nets simulation. The use of this approach will lead us to deal with different disturbances. Indeed, for any disturbance we should calculate a new schedule and a new polynomial will be found. This polynomial will be assigned to Petri nets model without modifying its structure.

SIMULATION , DESIGN AND PRACTICAL IMPLEMENTATION OF A MOBILE WIRELESS AUTONOMOUS SURVEILLANCE SYSTEM

T.C. Manjunath, P.S. Shingare and S. Janardhanan

The paper presents the design, implementation of the a unique type of computer controlled wireless mobile surveillance robot equipped with intelligence. Building an experimental autonomous mobile wireless vehicle, which has the ability to perform in real time environments is both a technical and scientific challenge and demands the development of systems for perception, modeling, planning and navigation. Within this scope, this paper describes the construction of a low cost mobile autonomous robot, intended for educational and surveillance purposes. This is a technology demonstration work. The objective of the work is to design, fabricate each part and construct a mobile robot and control it with a computer through wireless link which would accomplish two dimensional motion on a horizontal plane, moving from one place to another, avoiding obstacles in its path of motion by using infra-red sensors and performing the pick and place motion. The work was undertaken as a sponsored consultation based project under the guidance of the author in the institute.

A SKELETON BASED METHOD FOR EFFICIENT 3D OBJECT LOCALIZATION - Application to teleoperation

Djamel Merad, Narjes Khezami, Malik Mallem and Samir Otmane

Our aim is to develop a vision system for teleoperation to localize an object. This system has to be used through Internet connection. The recognition problem addressed in this paper is to localize a 3D free-form object from a single 2D view of 3D scene. Using a skeletonization process allows to obtain two graphs, the first one representing an object in the scene (2D skeleton) and the second one representing a database object (3D homotopic skeleton). The method encodes geometric and topological information in the form of a skeletal graph and uses graph isomorphism techniques to match the skeletons and find the one-to-one correspondences of nodes in order to estimate the object’s pose. Knowing skeleton is a set of lines centred within the 3D/2D objects, our method transforms the problem of free form object localization into points and lines pose estimation. Some experimental results on real Images demonstrate the robustness of the proposed method with regard to occlusion, cluster, shadows …

A NEW PARADIGM FOR SHIP HULL INSPECTION USING A HOLONOMIC HOVER-CAPABLE AUV

Robert Damus, Samuel Desset, James Morash, Victor Polidoro, Franz Hover, Chrys Chryssostomidis, Jerome Vaganay and Scott Willcox

The XXX Lab, in collaboration with YYY, has undertaken the task of designing a new autonomous underwater vehicle (AUV), a holonomic hover-capable robot capable of performing missions where an inspection capability similar to that of a remotely operated vehicle (ROV) is the primary goal. Some shortcomings of the most common torpedo-like AUV have become clear, as interest has increased in using AUVs for new applications – those demanding close inspection, slow movement, and precise positioning. One of the primary issues in this mode of operating AUVs is how the robot perceives its environment and thus navigates. The predominant choices for navigating in close proximity to large iron structures, which precludes accurate fluxgate compass measurements, are all methods that require an AUV to receive position information updates from an outside source (i.e. LBL or USBL assisted location). The new paradigm we present in this paper divorces our navigation routines from any absolute reference frame except the depth of the robot. We argue that this technique offers substantial benefits over assistive-technology approaches, and will present the current status of our project.

AUTONOMOUS NAVIGATION ROBOTIC SYSTEM TO RECOGNIZE IRREGULAR PATTERNS

Danny Dos Santos, Rafael Peñalver and Wilmer Pereira

This paper presents an approximation of navigation problem under unknown environment using reinforcement learning. The motivation is to represent a robot that can move in a world with streets and intersections. Each intersection has a different quantity of streets (irregular blocks). The selected algorithms were Q-Learning and Value Iteration. The robot was programmed only with Q-Learning and we developed a simulation with both of them. This simulation allows making comparisons in order to determinate in which situation each algorithm is appropriate.

ROBUST IMAGE SEGMENTATION BY TEXTURE SENSITIVE SNAKE UNDER LOW CONTRAST ENVIRONMENT

Shu-Fai Wong and Kwan-Yee Kenneth Wong

Robust image segmentation plays an important role in a wide range of daily applications, like visual surveillance system, computer-aided medical diagnosis, etc. Although commonly used image segmentation methods based on pixel intensity and texture can help finding the boundary of targets with sharp edges or distinguished textures, they may not be applied to Images with poor quality and low contrast. Medical Images, Images captured from web cam and Images taken under dim light are examples of Images with low contrast and with heavy noise. To handle these types of Images, we proposed a new segmentation method based on texture clustering and snake fitting. Experimental results show that targets in both artificial Images and medical Images, which are of low contrast and heavy noise, can be segmented from the background accurately. This segmentation method provides alternatives to the users so that they can keep using imaging device with low quality outputs while having good quality of image analysis result.

VISUAL HAND MOVEMENTS FOR MACHINE CONTROL

Sanjay Kumar, Dinesh Kant Kumar and Arun Sharma

A new technique for automated classification of human hand gestures for robotics and computer control applications is presented. It uses view-based approach for representation, and statistical technique for classification. This approach uses a cumulative image-difference technique where the time between the sequences of Images is implicitly captured in the representation of action. This results in the construction of Temporal History Templates (THTs). These THT’s are used to compute the 7 Hu image moments that are invariant to scale, rotation and translation. The recognition criterion is established using K-nearest neighbor (K-NN) mahalanobis distance. The preliminary experiments show that such a system can classify human hand gestures with a classification accuracy of 92%. Our research has been carried on in the robotics framework. The overall goal of our research is to test for accuracy of the recognition of hand gestures using this computationally inexpensive way of dimensionality-reduced representation of gestures for its suitability for robotics.

ELECTROMYOGRAPHY BASED FINGER MOVEMENT IDENTIFICATION FOR HUMAN COMPUTER INTERFACE

Pah Nemuel D and Kumar Dinesh K

This paper reports experiments conducted to classify single channel Surface Electromyogram recorded from the forearm with the flexion and extension of the different fingers. Controlled experiments were conducted where single channel SEMF was recorded from the flexor digitorum superficialis muscle for various finger positions from the volunteers. A modified wavelet network called Thresholding Wavelet Networks that has been developed by the authors [10] has been applied for this classification. The purpose of this research was towards developing a reliable man machine interface that could have applications for rehabilitation, robotics and industry. The network is promising with accuracy better than 85%.

Eye Gaze for Computer Control

Dinesh Kant Kumar and E. Poole

This paper reports the results of experiments that were conducted with five subjects to determine the reliability of the use of Electroocular gram (EOG) for controlling computers. Experiments included vertical and horizontal eye motion. Consideration was given to identify a relationship between the angle of the gaze and signal that could be applied to cover all test subjects and generate the required spatial control signals. The results obtained are encouraging. An assessment of the data has concluded that the EOG can be successfully utilised for spatial control applications. The study recommends the choice of bandwidth for the recording, inter and intra subject reliability and difference between the vertical and horizontal movement control.

A VISUAL SERVOING ARCHITECTURE USING PREDICTIVE CONTROL FOR A PUMA560 ROBOT

Paulo Ferreira and João C. Pinto

A control system for a six degrees freedom Puma robot using a Visual Servoing architecture is presented. Two different predictive controllers, GPC and MPC, are used. A comparison between these two ones and the classical PI controller is performed. A new Robot puma model used as platform for the development of the control algorithms is presented. In this system the camera is placed on the robot’s end-effector and the goal is to control the robot pose to follow a target. A control law based on features extracted from camera Images is used. Simulation results show that the strategy works well and that visual servoing predictive control is faster than a PI control.

DIMSART: A REAL TIME - DEVICE INDEPENDENT MODULAR SOFTWARE ARCHITECTURE FOR ROBOTIC AND TELEROBOTIC APPLICATIONS

Jordi Artigas, Detlef Reintsema, Carsten Preusche and Gerhard Hirzinger

In this paper a Software Architecture for Robotic and Telerobotic applications will be described. The software is device and platform independent, and is distributed control orientated. Thus, the package will be suitable for any Real Time system configuration. The Architecture will allow designers to easily build complex Control Schemes, easily control and manage them, for any hardware device, and to communicate with other devices with a plug-in/plug-out modular concept. The need to create a platform where control engineers/ designers could freely implement their algorithms, without needing to worry about the device driver and about programing related topics, brought another goal to this project. Implementing a new control algorithm with the Software Architecture, here described, means just to follow a template where, the code itself that the designer has to write, is reduced to the implement the functions which have to do with the controller. We conducted several Teleopertation schemes, which will be here presented as some configuration example.

WIRELESS REMOTE MONITORING SYSTEM WITH FLEXIBLY CONFIGURABLE MULTIVISION

Shinichi Masuda and Tetsuo Hattori

Novel remote monitoring system for all day outdoor observation using wireless communication is proposed. It consists of three parts: a host station that is PC, remote station (camera and CPU) attached by solar cell and battery for power supply, and wireless sensor with ID signal. The remote station usually performs based on the event driven method by the sensor signal. It also can control the camera according to the sensor’s ID. So the multivision monitoring system is flexibly configurable. This paper describes the details of the system and evaluates the maximum number of connectable remote stations. Since the systems are now really running at many places in Japan, we regard that the fact shows its effectiveness in a practical sense.

A METHOD FOR HANDWRITTEN CHARACTERS RECOGNITION BASED ON A VECTOR FIELD

Tetsuya Izumi, Tetsuo Hattori, Hiroyuki Kitajima and Toshinori Yamasaki

In order to obtain a low computational cost method for automatic handwritten characters recognition, this paper proposes a combined system of two rough classification methods based on features of a vector field: one is autocorrelation matrix method, and another is a low frequency Fourier expansion method. In each method, the representation is expressed as vectors, and the similarity is defined as a weighted sum of the squared values of the inner product between input pattern and the reference patterns that are normalized eigenvectors of KL (Karhunen-Loeve) expansion. This paper also describes a way of deciding the weight coefficients based on linear regression, and shows the effectiveness of the proposed method by illustrating some experimentation results for 3036 categories of handwritten Japanese characters.

THE LASER SIGNATURE IN CALIBRATION OF THE SERVOMECHANISM

Edward Plinski, Antoni Izworski and Jerzy Witkowski

The laser signature is a specific physical phenomenon which appears in tuned CO2 lasers. In can be used as a standard for calibration of the servomechanism. The proposed servomechanism can be used for continuous investigations of the laser signatures of different laser media, and in that way can be spread into an expert system areas. The final aim is to find an optimum condition for the single frequency laser operation used for environmental investigations

AN APPLICATION OF THE INDEPENDENT COMPONENT ANALYSIS TO MONITOR ACOUSTIC EMISSION SIGNALS GENERATED BY TERMITE ACTIVITY IN WOOD

Juan José González de la Rosa, Isidro Lloret Galiana, Juan Manuel Górriz Sáez and Carlos García Puntonet

In this paper an extended robust independent components analysis (ERICA) algorithm based on cumulants is applied to identify vibrational alarm signals generated by soldier termites in southern Spain (reticulitermes grassei), by drumming their heads against the substratum, and measured by low cost equipment. A seismic accelerometer is employed to strongly characterize these acoustic emissions. To support the proposed technique, vibrational signals from a low cost microphone have been mixed with known signals, and the mixtures processed by ERICA. The experimental results confirm the validity of the proposed method, which has been taken as the basis for the development of a low cost, non-invasive, termite detection system

NEW DERIVATION OF THE FILTER AND FIXED-INTERVAL SMOOTHER WITH CORRELATED UNCERTAIN OBSERVATIONS

Seiichi Nakamori, Raquel Caballero-Águila, Aurora Hermoso-Carazo and Josefa Linares-Pérez

A least-squares linear fixed-interval smoothing algorithm is derived to estimate signals from uncertain observations perturbed by additive white noise. It is assumed that the Bernoulli variables describing the uncertainty are only correlated at consecutive time instants. The marginal distribution of each of these variables, specified by the probability that the signal exists at each observation, as well as their correlation function, are known. The algorithm is obtained without requiring the state-space model generating the signal, but just the covariance functions of the signal and the additive noise in the observation equation.

POLYNOMIAL ESTIMATION OF SIGNALS FROM UNCERTAIN OBSERVATIONS USING COVARIANCE INFORMATION

Seiichi Nakamori, Raquel Caballero-Águila, Aurora Hermoso-Carazo and Josefa Linares-Pérez

The least-squares vth-order polynomial filtering and fixed-point smoothing problems of uncertainly observed signals are considered. The proposed estimators do not require the knowledge of the state-space model generating the signal, but only the moments (up to the 2vth one) of the signal and the observation noise, as well as the probability that the signal exists in the observations.

ESTIMATION ALGORITHM FROM RANDOMLY DELAYED OBSERVATIONS WITH WHITE PLUS COLOURED NOISES

Seiichi Nakamori, Aurora Hermoso-Carazo, Josefa Linares-Pérez and María Isabel Sánchez-Rodríguez

A recursive algorithm for the least-squares linear one-stage prediction and filtering problems of discrete-time signals using randomly delayed measurements perturbed by additive white plus coloured noises are presented. It is assumed that the autocovariance function of the signal and the coloured noise are expressed in a semi-degenerate kernel form and the delay is modelled by a sequence of independent Bernoulli random variables, which indicate if the measurements arrive in time or are delayed by one sampling time. The estimators are obtained by an innovation approach and do not use the state-space model of the signal, but only the covariance information about the signal and the observation noises and the delay probabilities.

SIMULATION OF SYSTEMS WITH VARIOUS TIME DELAYS USING PADE'S APPROXIMATION

Mujo Hebibovic, Bakir Lacevic and Jasmin Velagic

In this paper, Pade's rational functions have been simulated for approximating several characteristic values of time delay regarding the plant time constant. Several representative plants were tested in order to show in which cases Pade’s function approximates time-delay block well. Only if the ratio of time delay versus time constant of the plant is rather great, or the plant contains emphasized numerator dynamics, approximation capabilities get poorer. The convergence rate of n-order Pade’s function has been also analyzed by using Taylor series and phase-frequency characteristics

A NEURAL NETWORK FRAMEWORK FOR IMPLEMENTING THE BAYESIAN LEARNING

Luminita State, Catalina Cocianu,Viorica Stefanescu and Vlamos Panayiotis

The research reported in the paper aims the development of a suitable neural architecture for implementing the Bayesian procedure for solving pattern recognition problems. The proposed neural system is based on an inhibitive competition installed among the hidden neurons of the computation layer. The local memories of the hidden neurons are computed adaptively according to an estimation model of the parameters of the Bayesian classifier. Also, the paper reports a series of qualitative attempts in analyzing the behavior of a new learning procedure of the parameters an HMM by modeling different types of stochastic dependencies on the space of states corresponding to the underlying finite automaton. The approach aims the development of some new methods in processing image and speech signals in solving pattern recognition problems. Basically, the attempts are stated in terms of weighting processes and deterministic/non deterministic Bayesian procedures. The aims were mainly to derive asymptotical conclusions concerning the performance of the proposed estimation techniques in approximating the ideal Bayesian procedure. The proposed methodology adopts the standard assumptions on the conditional independence properties of the involved stochastic processes

ON THE EFFICIENCY OF A CERTAIN CLASS OF NOISE REMOVAL ALGORITHMS IN SOLVING IMAGE PROCESSING TASKS

Catalina Cocianu, Luminita State, Vlamos Panayiotis and Viorica Stefanescu

The investigated noise removal algorithms are HRBA, HSBA, HBA, AMVR, PNRA, MMSE, MNR, MNR2 and NFPCA. The multiresolution support provides a suitable framework for noise filtering and for restoration purposes by noise suppression. The technique used in the paper is mainly based on the statistically significant wavelet coefficients specifying the support. The performed tests reveal that the use of the multiresolution support proves powerful and offers a versatile way to handle noise of different classes of distributions. The experimentally supported conclusions are reported in the final section of the paper. The research work reported in the paper aims to propose a new image reconstruction method based on the features extracted from the noise given by the principal components of the noise covariance matrix. The computation of the features of the noise h~ is carried out by a PCA neural network trained by the GHA as well as alternative approaches as for instance Generalized Recursive Least Square (GRLS) algorithm and APEX . The training process aims the learning of the p most significant eigen-vectors of S that is the eigenvectors corresponding to the largest p eigen-values of S.

CONTINUOUS-TIME SIGNAL FILTERING FROM NON-INDEPENDENT UNCERTAIN OBSERVATIONS

Seiichi Nakamori, Aurora Hermoso-Carazo, Jose Jiménez-López and Josefa Linares-Pérez

Filtering algorithms are presented as solution of the least mean-squared error linear estimation problem of continuous-time wide-sense stationary scalar signals from uncertain observations perturbed by white and coloured additive noises. These algorithms, one of them based on Chandrasekhar-type equations and the other on Riccati-type ones, are derived assuming a specific type of dependence between the Bernoulli random variables describing the uncertainty and do not require the whole knowledge of the state-space model. By comparing both algorithms it is deduced that the Chandrasekhar-type one is more advantageous from a computational viewpoint.

PARAMETRIC ESTIMATION OF SINUSOIDS IN NOISE - A comparison between parametric approaches and the definition of a regularized Smyth algorithm

Aldo Balestrino, Andrea Caiti and Roberto Mati

A comparison between well-established parametric algorithms and the more recent Smyth algorithm for estimation of sinusoidal signals in white noise is presented. The comparison is performed through a pseudo-Monte Carlo analysis on simulated data. The results obtained show that Smyth algorithm has a slightly better performance at large Signal-to Noise Ratios. However, when the SNR drops down, the performance of the Smyth algorithm dramatically decreases. A better performance with respect to both ESPRIT and Smyth algorithms at low SNR can be obtained by a regularized filtering procedure on the data.

MAP-MATCHING OF RADAR Images AND ELECTRONIC CHARTS USING THE HAUSDORFF DISTANCE

Tzu C. Shen and Andrés R. Guesalaga

This paper describes a new method of image pattern recognition based on the Hausdorff Distance. The technique looks for similarities between a given pattern and its possible representations within an image. This method performs satisfactorily when confronted to image perturbations or partial occlusions. An extension of the classical Hausdorff Distance technique chooses the best candidate among multiple sub-optimal solutions. The search strategy is based on the Branch and Bounds algorithm, where cells with low probability of containing the optimal solution are pruned, while feasible cells are divided again until the optimal solution is found. By using this strategy, exhaustive and no-informative searches are avoided among the possible combinations, reducing the processing time considerably. A case study is presented, where the proposed method is applied to calibration of surveillance radars using hydrographic charts as models for the radar echo Images

ADAPTIVE MIMO MULTI-PERIODIC REPETITIVE CONTROL SYSTEM: LIAPUNOV ANALYSIS

Hongwei Dang and David Owens

This paper presents a simple feed forward adaptive multi-periodic repetitive control scheme for the ASPR(Almost Strictly Positive Real) or ASNR(Almost Strictly Negative Real, See Appendix for definition) plant to asymptotically track/reject multi-periodic reference/disturbance signals. The Liapunov stability analysis is given. This is an extension work of the Liapunov stability analysis for multi-periodic repetitive control system under a positive real condition. A simulation is included. The extension of the Liapunov stability analysis to ASPR or ASNR plant under certain non-linear perturbations and an exponential stability scheme are discussed as well. Finally an adaptive proportional plus MRC(multi-periodic repetitive control) scheme is proposed.

ON MODELING AND CONTROL OF DISCRETE TIMED EVENT GRAPHS WITH MULTIPLIERS USING (MIN, +) ALGEBRA

Samir Hamaci, Jean-Louis Boimond and Sébastien Lahaye

Timed event graphs with multipliers, also called timed weighted marked graphs, constitute a subclass of Petri nets well adapted to model discrete event systems involving synchronization and saturation phenomena. Their dynamic behaviors can be modeled by using a particular algebra of operators. A just in time control method of these graphs based on Residuation theory is proposed.

DESIGN OF LOW DELAY BANDPASS FIR FILTERS WITH MAXIMALLY FLAT CHARACTERISTICS IN THE PASSBAND AND THE TRANSMISSION ZEROS IN THE STOPBAND

Yukio Mori and Naoyuki Aikawa

The large group delay of the high order FIR filters is unacceptable in some applications. Therefore, recently, how to reduce the group delay of FIR filters has been studied intensively. To reduce the ringing in the time domain and to maximize the stopband attenuation, it is useful to design FIR filters with maximally flat characteristics in the passband and transmission zeros in the stopband. We present a mathematically closed form transfer function of low delay bandpass FIR filters with maximally flat amplitude in the passband and the transmission zeros in the stopband. Because of the mathematically closed form transfer function, the designing filters are very simple. Moreover, we propose a design method of low delay bandpass FIR filters with maximally flat amplitude in the passband and equiripple in the stopband by using an iterative method of a closed form transfer function and Remez algorithm.

DYNAMIC STRUCTURE CELLULAR AUTOMATA IN A FIRE SPREADING APPLICATION

Alexandre Muzy, Eric Innocenti, Antoine Aïello, Jean-François Santucci, Paul-Antoine Santoni and David Hill

Study of complex propagation phenomena is performed through cellular simulation models. Usually cellular models are specific cellular automata developed by non-computer specialists. We attempt to present here a mathematical specification of a new kind of CA. The latter allows to soundly specify cellular models using a discrete time base, avoiding basic CA limitations (infinite lattice, neighborhood and rules uniformity of the cells, closure of the system to external events, static structure, etc.). Object-oriented techniques and DES are used to achieve this goal. The approach is validated in a fire spreading application.

STATE OBSERVER FOR NONLINEAR SYSTEMS: APPLICATION TO GRINDING PROCESS CONTROL

Seraphin C. Abou and Thien-My Dao

This paper discusses the way in which a state observer may be designed to control a special class of nonlinear systems. Focus is put on the pertinent applicability of the scope of these techniques, to control the dynamics of mills in mineral processes. The approach uses a small number of parameters to control the power draw affected by sudden changes within the system. This may be seen as the estimation of adjustable model parameters in order to fit the set of data where the form of the model does not need to be specified explicitly. It provides in principle ability to adapt to changing circumstances due to intermittent disturbances (like for instance changes in hardness of the raw material). Since the gain of the proposed observer depends on both the nonlinear and linear parts of the system, it improves the transient performance of the high gain observer. An acceptable performance and stability analysis was developed. Using a generalised similarity transformation for the error dynamics, it is shown that under a boundedness condition the proposed observer guarantees the global exponential convergence of the estimation error. This way, the nominal performance of the process is improved but the robust stability is not guaranteed to fully avoid the mill plugging.

ADAPTIVE SMITH PREDICTIVE CONTROL OF NON-LINEAR SYSTEMS USING NEURO-FUZZY HAMMERSTEIN MODELS

Jose Vieira and Alexandre Mota

This paper proposes an Adaptive Smith Predictor Controller (ASPC) based on Neuro-Fuzzy Hammerstein Models (NFHM) with on-line non-linear model parameters identification. The NFHM approach uses a zero-order Takagi-Sugeno fuzzy model to approximate the non-linear static function that is tuned off-line using gradient decent algorithm and to identify the linear dynamic function it is used the Recursive Least Square estimation with Reset of Covariance Matrix (RLSRCM). This algorithm has the capability of follow fast and slow dynamic parameter changes. The proposed ASPC has special capabilities to control non-linear systems that have gain, time delay and dynamic changes through time. The implementation of the ASPC is made in two steps: first, off-line estimation of the non-linear static parameters that will be used to “get linear” the non-linearity of the system and second, on-line identification of the linear dynamic parameters updating direct and inverse models used in the ASPC. As an illustrative example, a gas water heater system is controlled with the ASPC. Finally, the control results are compared with the results obtained with the Smith Predictive Controller based in a Semi-Physical Model (SPMSPC).

MODELLING AND PERFORMANCE EVALUATION OF DES - A MAX-PLUS ALGEBRA TOOLBOX FOR MATLAB

Jaroslaw Stanczyk, Eckart Mayer and Joerg Raisch

This paper discusses the usefulness of (max,+) algebra as a mathematical modelling framework for discrete event systems (DESs). A Max-Plus Algebra Toolbox is presented. This software package is a set of functions to take advantage of the (max,+) algebra in the Matlab environment for rapid prototyping, design, and analysis of DESs. An overview of the modelling and analysis concepts of the (max,+) algebra approach for DES is given. Application examples are provided in the final part of the paper to illustrate the potential of this approach and the toolbox.

IMPLEMENTATION OF A DEVICE COMPATIBLE WITH DIFFERENT FIELDBUSES USING RECONFIGURABLE CIRCUITS

Miguel Ángel Domínguez, Mª Dolores Valdés and Mª José Moure

Fieldbuses are serial communication networks very used in industrial control applications. They constitute the lower level of the communication networks in a flexible manufacturing system. Nowadays there are a lack of standardization in the area of fieldbuses and it supposes the existence of a lot of proprietary protocols. Thus, the interconnection of equipment from different manufacturers has become very problematic. It implies that a change in equipment supposes a change in the fieldbus too with the consequent economic losses. This paper proposes the implementation of a device using reconfigurable circuits such as FPGAs (Field Programmable Gate Arrays) that can be used as a communication processor, compatible with different fieldbuses making only little changes in the programming code and in the level and impedance matching circuit (depending on the electrical features of the corresponding fieldbus). Thus, the same hardware can be connected to different fieldbuses. The implementation of fieldbus communication processors using FPGAs implies that the interface can be easily adapted to different protocols (improvement in the interconnection between products of different manufacturers) and that the programming code can be easily modified, adding new functionality when it is necessary.

SPEAKER VERIFICATION SYSTEM Based on the stochastic modeling

Valiantsin Rakush and Rauf Kh. Sadykhov

In this paper we propose a new speaker verification system where the new training and classification algorithms for vector quantization and Gaussian mixture models are introduced. The vector quantizer is used to model sub-word speech components. The code books are created for both training and test utterances. We propose new approaches to normalize distortion of the training and test code books. The test code book quantized over the training code book. The normalization technique includes assigning the equal distortion for training and test code books, distortion normalization and cluster weights. Also the LBG and K-means algorithms usually employed for vector quantization are implemented to train Gaussian mixture models. Finally we use the information provided by two different models to increase verification performance. The system performance has been tested on the Speaker Recognition database, which consists of telephone speech from 4 participants.

IDENTIFYING AN OBSERVABLE PROCESS WITH ONE OF SEVERAL SIMULATION MODELS VIA UMPI TEST

Nicholas A. Nechval, Konstantin N. Nechval, Edgars K. Vasermanis and Kristine Rozite

In this paper, for identifying an observable process with one of several simulation models, a uniformly most powerful invariant (UMPI) test is developed from the generalized maximum likelihood ratio (GMLR). This test can be considered as a result of a new approach to solving the Behrens-Fisher problem when covariance matrices of multivariate normal populations (compared with respect to their means) are different and unknown. The test is based on invariant statistic whose distribution, under the null hypothesis, does not depend on the unknown (nuisance) parameters.

INTEGRATED DESIGN OF STRUCTURE/CONTROLLER FOR PARALLEL INVERTED PENDULUM SYSTEMS

Chiharu Ishii, Shigehiko Yamamoto and Hiroshi Hashimoto

An integrated design of structure/controller for parallel inverted pendulum systems is presented. In practical parallel inverted pendulum systems, existence of a realizable stabilizing controller is inevitably determined depending on the position of center of gravity of two pendulums. In this paper these parameters are set as structural parameters in structural systems and a descriptor form representation is used to express the dynamics of parallel inverted pendulum systems. A state feedback gain and structural parameters are determined based on a design of linear quadratic regulator(LQR), in which a generalized Ricatti equation in LQR problem for the descriptor form representation is reduced to LMI conditions. Main contribution of this paper is to give a method to determine the position of center of gravity of two pendulums for parallel inverted pendulum systems in a sense of suitable for control. Based on the obtained structural parameters, analysis on robustness and some experimental works are executed. Experimental results show the effectiveness of the proposed design method.

SOME FEASIBILITY ISSUES RELATED TO CONSTRAINED GENERALIZED PREDICTIVE CONTROL

Sorin Olaru and Didier Dumur

This paper analyzes the generalized predictive control law under constraints on the input, output or other auxiliary signals that depend linearly on the system variables. These constraints are formulated as sets of linear equalities or inequalities; the control sequence is therefore elaborated based on a quadratic optimization problem. The feasibility issues are related on one hand to the well posedness feature, and on the other hand to the compatibility with the set-point constraints. The prediction of the feasibility is of great interest from this point of view and necessary feasibility conditions are presented. Two possible approaches are followed, one strictly related to the specific set-point and the second, more general, examines the geo-metrical description of the optimization domain. The main practical advantage is that all the results are ba-sed on off-line numerical procedures offering qualitative information prior to the effective implementation.

FURTHER RESULTS ON OUTPUT FEEDBACK CONTROL OF DISCRETE LINEAR REPETITIVE PROCESSES

Bartłomiej Sulikowski, Krzysztof Galkowski, Eric Rogers and David H. Owens

Repetitive processes are a distinct class of 2D systems (i.e. information propagation in two independent directions) of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard (termed 1D here) or 2D systems theory. Here we give new results on the relatively open problem of the design of physically based control laws using an LMI setting. These results are for the sub-class of so-called discrete linear repetitive processes which arise in applications areas such as iterative learning control.

ZEROS, OUTPUT-NULLING SUBSPACES AND ZERO DYNAMICS IN MIMO LTI SYSTEMS Signal Processing, Systems Modelling and Control

Jerzy Tokarzewski and Lech Sokalski

In standard MIMO LTI systems S(A,B,C) the classical notion of the Smith zeros does not characterize fully the output-zeroing problem nor the zero dynamics. The question how this notion can be extended and related to the state-space methods is dicussed. The purpose of the paper is to present certain algebraic and geometric aspects of multivariable zeros that are not commonly known from the relevant literature.

MODEL PREDICTIVE CONTROL FOR HYBRID SYSTEMS UNDER A STATE PARTITION BASED MLD APPROACH (SPMLD)

Jean Thomas, Didier Dumur, Jean Buisson and Herve Guéguen

This paper presents the State Partition based Mixed Logical Dynamical (SPMLD) formalism as a new modeling technique for a class of discrete-time hybrid systems, where the system is defined by different modes with continuous and logical control inputs and state variables, each model subject to linear constraints. The reformulation of the predictive strategy for hybrid systems under the SPMLD approach is then developed. This technique enables to considerably reduce the computation time (with respect to the classical MPC approaches for PWA and MLD models), as a positive feature for real time implementation. This strategy is applied in simulation to the control of a three tanks benchmark.

A NOVEL REPETITIVE CONTROL ALGORITHM COMBINING ILC AND DEAD-BEAT CONTROL

Christopher Freeman, Paul Lewin, Eric Rogers, Jari Hätönen, Tom Harte and David Owens

In this paper it is explored whether or not a well-known adjoint Iterative Learning Control (ILC) algorithm can be applied to Repetitive Control (RC) problems. It is found that due to the lack of resetting in Repetitive Control, and the non-causal nature of the adjoint algorithm, the implementation requires a truncation procedure that can lead to instability. In order to avoid the truncation procedure, as a novel idea it is proposed that dead-beat control can used to shorten the impulse response of the plant to be so short that the need for truncation is removed. Therefore, convergence is guaranteed, if the adjoint algorithm is applied to the closed-loop plant with a dead-beat controller. The proposed algorithm is validated using real-time experiments on a non-minimum phase spring-mass-damper system. The experimental results show fast convergence to near perfect tracking, demonstrating the applicability of the proposed algorithm to industrial RC problems.

FROM DIOID ALGEBRA TO P-TIME EVENT GRAPHS

Mohamed Khalid Didi Alaoui and Philippe Declerck

The consideration of time in the modelling leads to different models as PERT graphs, P-time Petri nets and Time Stream Petri Nets which extend Timed Petri Nets and generalize the semantic of its synchronization. The aim of this paper is to present a new class of model in the field of topical algebra which unifies these time models: the interval descriptor system The cycle-time vector allows us to verify the solution existence of the system and to check its behaviour, particularly the liveness of the transition in an horizon. In this paper, we consider the p-time event graphs which is an example of interval descriptor system.

WATER SUPPLY REMOTE MONITORING SYSTEM: A CASE STUDY

Henrique Proença, Fernando Ribeiro, J.C. Metrôlho and Ricardo Oliveira

In recent years, there has been enormous research interest in natural resources monitoring. So, there is a need to develop easily accessible, cheap and reliable information systems for monitoring and early warning, which could be used in most natural resources. This paper presents an ongoing information system development that aims the monitoring and supervising of some parameters on water supply, such as quality and quantity. To implement our system we use several technologies in order to monitoring about 100 water tanks in an area of ±1000 Km2. In these technologies is included GSM communication, web infrastructure and sensing equipment that allows the access of information from any place of the world. In paper sections the main blocks of the system architecture are described in detail

STRUCTURED INFORMATION PROCESSING FOR SELF-OPTIMIZING MECHATRONIC SYSTEMS

Thorsten Hestermeyer, Oliver Oberschelp and Holger Giese

Self-optimizing mechatronic systems are based on intrinsic controller systems whose complexity by far exceeds that of currently available systems. In addition to procedures taken from artificial intelligence, procedures for a reconfiguration by means of appropriate design methods have to be integrated to fully implement self-optimization features. Special importance falls to a networking of such complex controller systems for the support of collaborative and emergent self-optimization. One main challenge lies in the safety-critical nature of the systems that requires the resulting software along with the technical system to show a predictably correct behavior in spite of networking, reconfiguration, and integration of procedures from artificial intelligence. The paper presents a concept for structuring and designing reconfigurable controller systems.

MULTIRATE OUTPUT FEEDBACK BASED DISCRETE-TIME SLIDING MODE CONTROL FOR A CLASS OF NONLINEAR SYSTEMS

Sivaramakrishnan Janardhanan, Bijnan Bandyopadhyay and Prashant Shingare

The property of certain nonlinear continuous-time systems to be exactly representable in discrete-time is known as finite discretizability. This paper presents a method for the discrete-time sliding mode control for nonlinear systems that are finitely discretizable.

IMPROVING PERFORMANCE OF THE DECODER FOR TWO-DIMENSIONAL BARCODE SYMBOLOGY PDF417

Hee Il Hahn and Jung Goo Jung

In this paper we introduce a method to extract the bar-space patterns directly from the gray-level two-dimensional barcode Images, which employs the location and the distance between extreme points of profiles scanned from the barcode image. This algorithm proves to be very robust from the high convolutional distortion environments such as defocussing and warping, even under badly illuminating condition. The proposed algorithm shows excellent performance and is implemented in real-time.

AN ACCURATE AND EFFICIENT PARAMETER DECOUPLING FOR TRANSFER FUNCTION IDENTIFICATION

In-Yong Seo and Allan E. Pearson

We present an improved parameter decoupling algorithm in estimating parameters that characterize the numerator and denominator of transfer function polynomials using the Adaptive Weighted Least Squares arising (AWLS) and Weighted Least Squares (WLS) from Fourier moment functionals of the Shinbrot type. This algorithm gives more accurate estimates and uses less computation than Pearson’s algorithm. Also, simulation examples show that this algorithm can be applied to the frequency analysis of lightly damped systems for which establishing steady state or stationary operation may require unreasonably long settling times

INVARIANT FEATURES FOR CHARACTER RECOGNITION

Ryszard S. Choras

This paper presents feature extraction method for recognition isolated characters. Feature extraction is most important factor in achieving high recognition performance. We presented moment invariants as features for pattern recognition. This article analysis the image feature extraction task on the basis of moments invariants for image recognition problem.

A PRO-ACTIVE RESOLVER MODEL TO COPE WITH PARAMETER VARIABILITY IN THE MANUFACTURING CHAIN

João Figueiredo and José Sá da Costa

In this paper a linearized model for Pancake resolvers is developed with the aim of compensating deviations on manufacturing inputs through computed corrections on the production controllable variables, mainly winding parameters. This model follows a two-step strategy where at the first step an accurate model computes the resolver nominal conditions and at a second step a linearized model based on production controllable variables computes the corrections on these controllable variables in order to compensate small deviations on the nominal conditions due to processes variability in the manufacturing. This model had been simulated and experimentally tested in a Siemens resolver manufacturing plant. The tests done proved the efficiency of the developed model and its usefulness in stabilizing the product specifications in a dynamic environment with high variability of manufacturing processes.

ACTIVE ACOUSTIC NOISE CONTROL IN DUCTS

Filipe Morais and J. M. Sá da Costa

In this paper existing classical and advanced techniques of active acoustic noise cancellation (ANC) in ducts are collected and compared. The laboratory plant used in experience showed a linear behaviour and so the advanced techniques were not used. Due to delay on the plant, the feedback classical techniques could not be applied. The best results were obtained with the modified filtered-reference LMS (MFX-LMS) and filtered-u techniques. A very important conclusion is that the quadratic normalisation is needed to maintain the algorithms always stable. In this paper 18dB of attenuation of white noise and full attenuation of tonal noise were achieved. Thus, ANC can be applied in a real situation resulting in important noise attenuations.

STABILIZING CONTROL FOR HIGHER ORDER SYSTEMS VIA REDUCED ORDER MODEL - A PASSIVITY BASED APPROACH

Bijnan Bandyopadhyay, Prashant Shingare and H. K. Abhyankar

In this paper a methodology for the design of stabilizing control for the high order system via reduced order model is presented. In the first part a method is proposed for the reduction of the original higher order passive system to a lower order stable model, using this reduced order model, a strictly passive controller of order equal to that of reduced order model is designed. It is shown that this lower order controller designed from the reduced order model when applied to the original higher order system results in close loop stability.

HYBRID UML COMPONENTS FOR THE DESIGN OF COMPLEX SELF-OPTIMIZING MECHATRONIC SYSTEMS

Sven Burmester, Holger Giese and Oliver Oberschelp

Complex technical systems, such as mechatronic systems, can exploit the computational power available today to achieve an automatic improvement of the technical system performance at run-time by means of self-optimization. To realize this vision appropriate means for the design of such systems are required.To support self-optimization it is not enough just to permit to alter some free parameters of the controllers. Furthermore,support for the modular reconfiguration of the internal structures of the controllers is required. Thereby it makes sense to find a representation for reconfigurable systems which includes classical, non-reconfigurable block diagrams. We therefore propose hybrid components and a related hybrid Statechart extension for the Unified Modeling Language (UML); it is to support the design of self-optimizing mechatronic systems by allowing specification of the necessary flexible reconfiguration of the system as well as of its hybrid subsystems in a modular manner.

MATLAB MODELS OF ACMS IN CONTROL SYSTEMS

Fei Hao, Fei Xia, E. Graeme Chester, Alex Yakovlev and Ian G. Clark

Asynchronous communication mechanisms (ACMs) are potentially useful in systems with heterogeneous timing as data connectors between processes belonging to different timing domains. In distributed, concurrent and embedded digital systems, there is often a desire to have some temporal decoupling between different parts of a system. ACMs provide a means with which concurrent processes can communicate with one another and yet still avoid synchronization. This paper describes efforts to implement MATLAB-based models of existing ACM algorithms. These techniques will facilitate the inclusion of ACMs in such application fields as distributed control and signal processing systems.

STATE-DEPENDENT DELAY SYSTEM MODEL FOR CONGESTION CONTROL

Konstantin E. Avrachenkov and Wojciech Paszke

This paper considers the problem of the stability for a control system with a state-dependent delay. Systems with state-dependent delays arise naturally in the data network congestion control schemes. Simple analytical studies of stability are provided for a particular set of initial conditions. Then, to verify these results and to extend the stability analysis, the Simulink-based simulator is presented and described. The developed simulator allows us to extend stability analysis for a variety of sets of initial conditions.

EFFICIENT SYSTEM IDENTIFICATION FOR MODEL PREDICTIVE CONTROL WITH THE ISIAC SOFTWARE

Paolino Tona and Jean-Marc Bader

ISIAC (as Industrial System Identification for Advanced Control) is a new software package geared to meet the requirements of system identification for model predictive control and the needs of practicing advanced process control (APC) engineers. It has been designed to naturally lead the user through the different steps of system identification, from raw data to ready-to-use models. Each phase can be performed with minimal intervention and maximum speed, yet the user has every freedom to experiment with the many options available. The underlying estimation approaches, based on high-order ARX estimation followed by model reduction, and on subspace methods, have been selected for their capacity to treat the large dimensional problems commonly found in system identification for process control, and to produce fast and robust results. Models describing parts of a larger system can be combined into a composite model describing the whole system. This gives the user the flexibility to handle complex model predictive control configurations, such as schemes involving intermediate process variables.

MOMENT-LINEAR STOCHASTIC SYSTEMS

Sandip Roy, George C. Verghese and Bernard C. Lesieutre

We introduce a class of quasi-linear models for stochastic dynamics, called moment-linear stochastic systems. We formulate MLSS and analyze their dynamics, as well as discussing common stochastic models that can be represented as MLSS. Further studies, including development of optimal estimators and controllers, are summarized. We discuss the reformulation of a common stochastic hybrid system---the Markovian jump-linear system---as an MLSS, and show that the MLSS formulation can be used to develop some new analyses for MJLS. Finally, we briefly discuss the use of MLSS in modeling certain stochastic network dynamics. Our studies suggest that MLSS hold promise in providing a framework for modeling interesting stochastic dynamics in a tractable manner.

CONTEXT IN ROBOTIC VISION: CONTROL FOR REAL-TIME ADAPTATION

Paolo Lombardi, Virginio Cantoni and Bertrand Zavidovique

Nowadays, the computer vision community conducts an effort to produce canny systems able to tackle unconstrained environments. However, the information contained in Images is so massive that fast and reliable knowledge extraction is impossible without restricting the range of expected meaningful signals. Inserting a priori knowledge on the operative “context” and adding expectations on object appearances are recognized today as a feasible solution to the problem. This paper attempts to define “context” in robotic vision by introducing a summarizing formalization of previous contributions by multiple authors. Starting from this formalization, we analyze one possible solution to introduce context-dependency in vision: an opportunistic switching strategy that selects the best fitted scenario among a set of pre-compiled configurations. We provide a theoretical framework for “context switching” named Context Commutation, grounded on Bayesian theory. Finally, we describe a sample application of the above ideas to improve video surveillance systems based on background subtraction methods.

STABILITY ANALYSIS AND SIMULATIONS OF A CLASS OF CONTINUOUS LINEAR 2D SYSTEMS

Blazej Cichy, Krzysztof Galkowski, Artur Gramacki, Jaroslaw Gramacki and Gerhard Jank

In the paper the problem of stability and stabilization of a~class of continuous bidirectional systems has been considered. The system has been described in the form of a continuous linear 2D model. The LMI approach has been successfully applied to the problem. Sufficient conditions of stability has been stated and proofed. Moreover some simulation results have been appended in the last section.

A STOCHASTIC MODEL OF PASSENGER TRANSPORT

Klara Janglajew and Olga Lavrenyk

We develop a stochastic model in which a recursive formula is derived for computing the mean value of income from sales of bus tickets. The model takes into consideration basic variable costs (driver's wages and fuel for the bus) and the flow of passengers is given by a Possion process. The recursive formula for a income is in the form of a linear discrete system with a random inhomogeneous part.

EXPLORING THE LINEAR RELATIONS IN THE ESTIMATION OF MATRICES B AND D IN SUBSPACE IDENTIFICATION METHODS

Catarina J. M. Delgado and P. Lopes dos Santos

In this paper we provide a different way to estimate matrices B and D, in subspace identification algorithms. The starting point was the method proposed by Van Overschee and De Moor (1996) -- the only one applying subspace ideas to the estimation of those matrices. We have derived new (and simpler) expressions and we found that the method proposed by Van Overschee and De Moor (1996) can be rewritten as a weighted least squares problem, involving the future outputs and inputs.

RECURSIVE MOESP TYPE SUBSPACE IDENTIFICATION ALGORITHM

Catarina J. M. Delgado and P. Lopes dos Santos

In this paper two recursive algorithms, based on MOESP type subspace identification, are presented in two versions. The main idea was to show that we can represent subspace identification methods as sequences of least squares problems and implement them through sequences of modified Householder algorithms. Therefore, it is possible to develop iterative algorithms with most of the advantages of this kind of methods, and still improve the numerical efficiency, in order to deal with real-time applications and minimize the computational burden.

NEW METHOD FOR STRUCTURAL CHANGE DETECTION OF TIME SERIES AS AN OPTIMAL STOPPING PROBLEM

Hiromichi Kawano, Ken Nishimatsu and Tetsuo Hattori

Even if an appropriate prediction expression and/or model is constructed to fit a time series, the model generally begins to unfit the time series from some time point, especially in the field that relates to human activity and social phenomenon. In such case, it will be important not only to quickly detect the unfitting situation but also to rebuild the prediction model after the detection as soon as possible. In this paper, we formulate the structural change detection problem in time series as an optimal stopping problem with a cost function that is the sum of unfitting loss and action cost after the detection. And we propose a method for optimal solution and show the correctness by proving a theorem. Also we clarify the effectiveness by showing the numerical experimentation.

A Comparative Study Between Neural Network and Maximum Likelihood in the Satellite Image Classification

Antonio Gabriel Rodrigues, Rossana Baptista Queiroz and Arthur Tórgo Gómez

In this paper it's showed a comparative study between two techniques of satellite image classification. The studied techniques are the Maximum Likelihood statistical method and an Artificial Intelligence technique based in Neural Networks. The analysed Images were scanned by CBERS 1 satellite and supplied by Brazilian National Institute for Space Research (INPE). These Images refer to Province of Rondonia area and were obtained by CBERS 1 IR-MSS sensor.

Flood Forecasting Using Neural Networks

A. R. Ghumman, U. Ghani and M. A. Shamim

This paper deals with flood routing in rivers using neural networks. The unsteady river flow may be formulated in terms of two one dimensional partial differential equations. These are the Saint Venant flow continuity and dynamic equations. Several methods of solution of these equations are known. These methods are based upon characteristics of equations, finite difference, finite element and finite volume. All of these methods have some limitations regarding data requirements and complications involved in solution of equations. Neural network techniques have been developed recently. These are easy to use and need comparatively less data and less labor for solution of the problem. One of these techniques is used in this research work. The model was applied for flood routing in River Chenab in Pakistan. Its reach from Marala to Khanki was selected. Date for various flood events was collected from Meteorological Department, Lahore and Flood Commission Islamabad. The error between the observed and simulated values of flood hydrograph ordinates was found to be in acceptable range.

Neuro-Controller with Simultaneous Perturbation for Robot Arm - Learning of Kinematics and Dynamics without Jacobian

Yutaka Maeda, Nobutaka Kitajima, Tsubasa Inagaki and Hidenori Onishi

We report two control schemes for a two-link robot arm system using a neuro-controller. We adopted the simultaneous perturbation learning rule for a neuro-controller. Ordinary gradient type of learning rule uses Jacobian of the objective system in a direct control scheme. However, the learning rule proposed here requires only two values of an error function. Without Jacobian or related information of the objective robot arm, the neuro-controller can learn an inverse of robot kinematics and dynamics, simultaneously. Some results are shown.

Comparison of ART-2 and SOFM Based Neural Network Verifiers

Pavel Mautner, V. Matousek, T. Marsalek and O. Rohlik

The Carpenter-Grosberg’s ART-2 and Kohonen’s Self-organizing Feature Map (SOFM) have been developed for the clustering of input vectors and have been commonly used as unsupervised learned classifiers. In this paper we describe the use of these neural network models for signature verification. The biometric data of all signatures were acquired by a special digital data acquisition pen and fast wavelet transformation was used for feature extraction. The part of genuine signature data was used for training both signature verifiers. The architecture of the verifiers and achieved results are discussed here and ideas for future research are also suggested.

A Study of Neural and Fuzzy Parameters for Explicit and Implicit Knowledge-based Systems

Daniel C. Neagu

A framework of a unified neural and neuro-fuzzy approach to integrate implicit and explicit knowledge in hybrid intelligent systems is presented. In the developed hybrid system, training data is used to develop neural and neuro-fuzzy models, and represents implicit domain knowledge. On the other hand, the explicit domain knowledge is represented by fuzzy rules, directly mapped into equivalent neural structures. A formal model for a hybrid intelligent system based on implicit and explicit knowledge implemented as neural, neuro-fuzzy and fuzzy modules is proposed. This paper explores also the influence of the main identified parameters of the proposed model on the accuracy of the hybrid intelligent system in a predictive data mining application.

Enlarging Training Sets for Neural Networks

Roberto Gil-Pita, Pilar Jarabo-Amores, Manuel Rosa-Zurera and Francisco López-Ferreras

A study is presented to compare the performance of multilayer perceptrons, radial basis function networks, and probabilistic neural networks for classification. In many classification problems, probabilistic neural networks have outperformed other neural classifiers. Unfortunately, with this kind of networks, the number of required operations to classify one pattern directly depends on the number of training patterns. This excessive computational cost makes this method difficult to be implemented in many real time applications. On the contrary, multilayer perceptrons have a reduced computational cost after training, but the required training set size to achieve low error rates is generally high. In this paper we propose an alternative method for training multilayer perceptrons, using data knowledge derived from the probabilistic neural network theory. Once the probability density functions have been estimated by the probabilistic neural network, a new training set can be generated using these estimated probability density functions. Results demonstrate that a multilayer perceptron trained with this enlarged training set achieves results equally good than those obtained with a probabilistic neural network, but with a lower computational cost.

Neural Networks and Rainfall-Runoff Model, its Calibration and Validation

U.Ghani, A.R. Ghumman and M.A.Shamim

In this study a rainfall-runoff model was developed with the help of neural networks. Input to the model is precipitation and potential evapotranspiration (both on monthly basis). Output from the model is the simulated runoff at the watershed outlet. The model was calibrated and tested for Brandu river catchment of Pakistan. The data was collected from Meteorological Department Pakistan. Statistical results showed that the model preformed well. The correlation co-efficient between the simulated and measured data was found to be 87.5%.

On the Capability of Neural Networks to Approximate the Neyman-Pearson Detector: A Theoretical Study

Pilar Jarabo-Amores, Roberto Gil-Pita, Manuel Rosa-Zurera and Francisco López-Ferreras

In this paper, the application of neural networks for approximating the Neyman-Pearson detector is considered. We propose a strategy to identify the training parameters that can be controlled for reducing the effect of approximation errors over the performance of the neural network based detector. The function approximated by a neural network trained using the mean squared-error criterion is deduced, without imposing any restriction on the prior probabilities of the clases and on the desired outputs selected for training, proving that these parameters play an important role in controlling the sensibility of the neural network detector performance to approximation errors. Another important parameter is the signal-to-noise ratio selected for training. The proposed strategy allows to determine its best value, when the statistical properties of the feature vectors are known. As an example, the detection of gaussian signals in gaussian interference is considered.

Global Path Planning Based on Neural Network and Genetic Algorithm in A Static Environment

Huahua Chen, Xin Du and Weikang Gu

Mobile robot global path planning in a static environment is an important problem all along. The paper proposes a method of global path planning based on neural network and genetic algorithm. The neural network model of environmental information in the workspace for a robot is constructed. Using this model, the relationship between a collision avoidance path and the output of the model is established. Then the two-dimensional coding for the via-points of path is converted to one-dimensional one and the fitness of both the collision avoidance path and the shortest distance are fused to a fitness function. The simulation results show that the proposed method is correct and effective.

Distributed Control Lab

Andreas Rasche, Bernhard Rabe, Peter Tröger and Andreas Polze

The Distributed Control Lab (DCL) provides an open infrastructure for conducting robotics and control experiments from the Internet. It is based on web service technologies and offers a wide range of frontend applications. Within the DCL environment we focus on safety mechanisms in order to prevent malicious code from damaging experimental equipment. This includes source code analysis, runtime observation and the dynamic replacement of faulty control algorithms. Within the paper we present an overview of our architecture and explain the implemented frontends in detail. We introduce the installed experiments and report our experiences from operation in the last years. In addition we will describe our latest integration of grid computing technologies, which allows the outsourcing of computing-intensive simulation tasks.

A Remote RF Laboratory in Electrical Engineering Education

Daniel Courivaud

This paper describes the use of a hardware and software environment that allows distant access to RF electronics measurement devices called Remote RF Laboratory. This access only requires conventional Internet browser and corresponding plug-in, both available for free, and low speed Internet connexion. Remote users may perform web-based RF measurements at any time, from any place, which is particularly interesting for applications in distant learning, enhancement of traditional lectures and from a financial point of view. General architecture of the remote laboratory is presented and multiple accesses to it discussed. Pedagogical approach is described and advantages compared to traditional lab are outlined. Users feedback is given and discussed.

Remote Control and Reconfiguration of Laboratories for Education and Training

Wolfgang Burgstaller, Olga Plaxina and Kirill Seleznev2

Organizing practical courses and training clearly indicates a demand for remote training. This article describes the concepts of the BACnet (Building Automation Control Network) laboratory being set up by the authors. To allow effective learning the control network (fieldbus) as well as the inputs and out-puts of the nodes attached to the laboratory environment must be accessible by the trainee. To achieve this goal a web based application which uses a VNC (Virtual Network Computing) server and a special I/O interfacing unit have been designed. Hence, trainees will be able not only to monitor and control the activities on the control network (the primary goal of the offered courses) but also will be able to see the effects of their activities on the laboratory environ-ment.

Analysis of Experience: Fully Web Based Introductory Course in Electrical Engineering

Vello Kukk

This paper summarizes analysis of the experience obtained form teaching large student group using fully web-based tools. General descriptions and formal parameters of the course along with numerical data concerning numbers of different actions are given. Analysis of collected data and changes in students' opinions are presented. Some critical conclusions are given concerning the role of lectures and lab works are made. Problems related to university's information system are also concerned.

Remote Laboratory for Industrial Automation

Rui Delgado, Gustavo Santos, Carlos Cardeira, J. R. C. Pinto, Rui Loureiro and Otto Leichsenring

In this paper we present a remotely accessed experiment on industrial automation. Using this remote access, students may verify the correctness of their previous work and increase the productivity of laboratory classes. The experiment provides a web page for interfacing with a Programmable Logic Controller (PLC) which controls an electro-pneumatic process. Students may remotely download the program to the PLC and access to the PLC states and variables remotely, allowing the detection of semantic errors. Moreover a Webcam shows the image of the process which, not being essential, provides a more realistic view of the program correctness. The user has access to the system inputs through a web based HMI. This paper results from collaboration between a PLC solution provider and the university.

Lookup-based Remote Laboratory for FPGA Digital Design Prototyping

Leandro Soares Indrusiak, Manfred Glesner and Ricardo Augusto da Luz Reis

This paper presents an approach that allows sharing and remote usage of FPGA prototyping boards, aiming to an efficient and simplified access to the board resources by students and designers. A lookup service hides the complexity of the distribution of the boards over the network, while a proxy-based access interface abstracts the internals of each board, allowing integration at the API level.

Didactical Software Tools on Electrical Circuits and Electrical Machines, Produced in the Frame of the Leonardo Da Vinci Pilot Project “Virtual-Electro-Lab”

Gheorghe SCUTARU, Leão RODRIGUES, Paul RAES and Dan SOREA

The presented software tools have been accomplished in the frame of the Leonardo da Vinci pilot project “Virtual-Electro-Lab”. The goal of the project consists of developing a complex training system in electrical domain that includes the correlation of the courses, seminars / workshops and testing sys-tems with the virtual & remote experiment elements. It proposes an innovative approach of the teaching method using a virtual & remote laboratory and sup-poses the setting up of new ICT software tools for training in order to imple-ment this innovative approach

eLearning Tool for Adults Training on Renewable Energy Systems Developed in the Leonardo Da Vinci Project RES&EM ICT Tools

A. Duta, I. Visa, E. B. Fazakas and G. Scutaru

The paper presents the eLearning tool developed in the frame of the Leonardo da Vinci pilot project “Renewable Energy Sources and Environment Friendly ICT Tools – RES&EM ICT Tools”. This product aims to offer training and information to a broad spectrum of target groups, with different education background and interest, in a subject able to support the (re)insertion in the working market, either as worker or as entrepreneur/manager

The Database and Architecture of Virtual and Remote Laboratories - Implementations in the Virtual Electro Lab Project

Sorin Moraru, Ionut Diaconu, Adrian Pelcz and Silviu Leahu

This paper treats the database structure and the architecture of “Virtual ElectroLab”. The “Virtual ElectroLab” makes use of a relational database (MS SQL). It is also covered the communication procedure between the client and server. The article describes the database structure exemplified through the database diagram. The web-based experiments are executed in an asynchronous mode.

Remote Experiments Using Java - Implementations in the Virtual Electro Lab Project

Adrian Pelcz, Francisc Sisak, Sorin Moraru, Silviu Leahu and Ionut Diaconu

This paper treats the e-learning domain from the virtual and remote laboratories point of view. These laboratories have Java applets as client side application. The paper presents the importance of offering to students the possibility to do laboratory tests with real data. Although a remote experiment can not provide the student with the real feedback of the experiment, by using real data and a good representation of the laboratory equipment, we can get closer the the real feedback. The article describes the facilities offered by the Java language in making user interfaces for the remote and virtual laboratories. At the same time, we present three implementations in the pilot project "VirtualElectroLab" of the "Leonardo da Vinci" program that have user interfaces based on the Java Applet technology, for accessing the laboratory resources via Internet.

Security Aspects in Virtual and Remote Laboratories - Implementations in the Virtual Electro Lab project

Silviu Leahu, Sorin Moraru, Adrian Pelcz and Liviu Perniu

When it comes about accessing an application remotely, that is from another computer than that where the application resides, the security should always be of concern. Because the connection between the two computers is done through a physical space, on which we may not have any control, whether that connection is through wires or wireless, we must be on guard of any possible identity and information stealing. This paper deals with the security aspect encountered in any remotely communication between two or more computers, connected among them through a physical or wireless connection. It explains the theoretical base and the implementation of these aspects in “VirtualElectroLab”.

A Robotic Set-Up With Remote Access For "Pick and Place" Operations Under Uncertainty Conditions

Aldo Balestrino, Antonio Bicchi, Andrea Caiti, Torquato Cecchini, Lucia Pallottino, Andrea Pisani and Giovanni Tonietti

The work describes on-going work at the University of Pisa on the field of tele-laboratories and distance learning. In particular, the group is working at the evolution of existing tele-laboratory experiments in the field of robotics and control into learning units of a self-consistent didactic project. The pick-and-place system described has been designed to provide the set-up for robot arm motion planning with specific objectives and evaluation tools.

EDBI – An E-Learning Based Project to Improve Engineering Teaching

Carlos Pais, V. Fernão Pires, Rui Amaral, João Martins, Carlos Luz and O. P. Dias

Elevated rates of failure in Engineering courses at the university level, in addition to the difficulty in attracting new students to courses in this area have made it necessary to implement new and innovative measures to invert this trend. ‘EDBI’ (Ensino à Distância Baseado na Internet) is a project conceived with the purpose of increasing school success and capturing the interest of the students through the implementation of a computer-assisted teaching solution which acts as a pedagogic tool and is used to complement the other traditional teaching methods commonly used when teaching mathematics, electrical and electronics. Aside from the context and goals that were the motive for this project, the strategies and lines of orientation followed in the implementing of the solution, as well as its phases, steps and organization in the current phase of its development will also be described. In addition, it will also explore the alterations that this type of strategy may cause in the roles traditionally attrib-uted to teachers and students, and the effect that these changes bring about in the teacher-student relationship, and in the responsibilities of each. Finally, it will present the principle conclusions obtained up until now.

An Environment for Remote Control

Paulo Almeida, Fernando Coito and Luís Palma

This paper presents an environment for monitoring and control of remote systems. The aim of this work is the development of software for virtual laboratories, and e-learning. The architecture based on a server and multiple clients, runs on a LabView® platform. Remote clients can monitor and control remote process models or real systems linked to the server, via the TCP/IP protocol. The ERC system, under development, is appropriate for control education and allows the use of different type of controllers, such as PID, Fuzzy, and others, implemented in the Matlab® language.

Virtual Remote Measurement of Controlled Sources

Florin Sandu, Gheorghe Scutaru, Ioan Emilian Cucerzan amd Daniel Iolu

A two level client-server development was performed by web layer (to send remote measurement stimuli + simulation parameters) and workbench layer – implemented under National Instruments “LabView” control. The test bench equipment allows both programming of signals generation / acquisition and PSpice simulation triggering. MS “FrontPage”- and Macromedia “Flash”-based string concatenation and Intranet local links in the “Network Neighbourhood” allow direct publishing of the web page that groups simulation results with those of remote experiments.

Implementation of a remote and virtual laboratory in the field of home appliance systems

Paul Nicolae Borza, Gheorghe Scutaru, Luís Gomes, Anikó Costa and Lazar Laszlo

One of the most dynamic branches of educational systems is linked with e-learning. In engineering, experiments play an important role in the learning process and, in general, impose student’s presence in laboratory in order to allow them to interact directly with instruments and objects under test. The pa-per presents some practical examples on how is possible to replace the tradi-tional laboratory with a remote and virtual laboratory in the field of home ap-pliance systems. The remote laboratory is based on two dedicated systems (named DomoControl128 and TinyDomots). Structure, main features and op-erational principles of current implementations are briefly presented

A FPGA Learning System combining Hardware and Software Tools

M. Dolores Valdés, M. José Moure, Camilo Quintáns, Bruno Pérez and Enrique Mandado

FPGA including very complex digital blocks are possible nowadays due to digital integrated circuits progress. FPGA fundamentals and characteristics are not easy to explain because they have a lot of interrelated concepts. By this reason FPGA learning is usually based on a family of a particular manufacturer and doesn’t give a general view of configurable devices. Due to that it is essential for the electronic learning community to dispose of tools facilitating the learning process of the fundamentals of the FPGA’s and the design of systems based on them. The learning system we describe in this paper combines a tutorial with a hardware and software tools to achieve a friendly interface with a PC to facilitate FPGA distance learning for students with a basic knowledge of digital electronics and VHDL

Analog Electronics Basic Simulator and Virtual Laboratory

Ángel Salaverría, Jacinto G. Dacosta, Luis F. Ferreira and Enrique Mandado

This paper describes a basic electronics learning system combining a hypermedia system explaining theoretical concepts with a basic simulator and a virtual laboratory to improve the engineering education process on electronics and the students skills before going to the actual laboratory. To accomplish this objective the system also provides a set of complementary resources, constituting a bridge between theory and practice. This new kind of hypermedia tools takes advantage of the information technologies (multimedia, simulation, etc.) and also facilitates the self assessment of the students knowledge.

Embedded Systems Introductory Course supported by remote experiments

Luis Gomes, Anikó Costa

Laboratories for introductory digital system design courses have, commonly, high rates of space and time occupation. In this paper, a remote laboratory is proposed in order to alleviate laboratory’s occupation, although increasing its usage by students. Its usage for supporting experimentation around a set of experiments with a set-up based on the 8031 microcontroller was successfully tested.