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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Yassine Bouteraa Gérard Poisson Jawhar Ghommam Nabil Derbel Institut PRISME Université d''Oran-Es-senia Bourges France Engineering School of Sfax (ENIS) Research unit on Intelligent Control design and Optimization of complex Systems (ICOS) University of Sfax Sfax Tunisia

We address the problem of designing decentralized laws to control a team of general fully actuated manipulators which synchronize their movements while following the same desired trajectory. To this effect we investigate an adaptive control of an identical multiple manipulators, with unknown inertia parameters, tracking a common trajectory. It is also assumed that all the robots in the synchronization system have the same number of joints and equivalent joint work spaces, i.e. any possible configuration of a given robot in the system can be achieved by any other robot in the system. Adaptive controls are derived for group of manipulators using a consensus algorithm. This consensus algorithm is applied on the group level to estimate the time-varying group trajectory information in a distributed manner. The proposed strategy only requires local neighbor-to-neighbor information exchange between manipulators and does not assume the existence of any explicit leaders in the team. The interaction topology of a network of agents is represented using an indirected graph. The coordination strategy is to let each manipulator track its desired trajectory while synchronizing its motion with the others manipulator's motions so that differential position errors amongst robots converge to zero.

关键词： Robot kinematics Synchronization Trajectory Manipulator dynamics Joints

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MLP neural network based face recognition system using constructive training algorithm

MLP neural network based face recognition system using const...

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IEEE International Conference on Multimedia Computing and systems (ICMCS)

作者： Hayet Boughrara Mohamed Chtourou Chokri Ben Amar Intelligent Control design and Optimization of complex Systems (ICOS) Sfax Engineering School BP W Sfax Sfax Research Group on Intelligent Machines (REGIM) Sfax Engineering School BP W Sfax

Face recognition is one of the most efficient applications of computer authentication and pattern recognition. Therefore it attracts significant attention of researchers. In the past decades, many feature extraction algorithms have been proposed. In this paper Gabor features and Zernike moment were used to extract features from human face images for recognition application. This paper is a study for new constructive training algorithm for Multi Layer Perceptron (MLP) which is applied to face recognition application. An incremental training procedure was employed where the training patterns are learned incrementally. This algorithm started with a single training pattern and a single hidden-layer using one neuron. During neural network training, the hidden neuron is increased when the Mean Square Error (MSE) of the Training Data (TD) is not reduced or the algorithm gets stuck in a local minimum. Input patterns are trained incrementally (one by one) until all patterns of TD are selected and trained. Face recognition system structure based on a MLP neural network was constructed and was tested for face recognition. The proposed approach was tested on the UMIST database. Experimental results indicate that we can obtain an optimal architecture of neural network classifier (with the least possible number of hidden neuron) using our present constructive algorithm, and prove the effectiveness of the proposed method compared to the MLP architecture with back-propagation algorithm.

关键词： Face Feature extraction Face recognition Neurons Gabor filters Image recognition

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Fuzzy predictive control of nonlinear systems

Fuzzy predictive control of nonlinear systems

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Widien Dhouib Mohamed Djemel Mohamed Chtourou Research Unit of Intelligent Control design & Optimisation of complex Systems (ICOS) National School of Engineering of Sfax University of sfax Sfax Tunisia

This paper presents two strategies of nonlinear predictive control based on a Takagi-Sugeno fuzzy model. The first one introduces a fuzzy logic-based modeling methodology, where a nonlinear system is divided into a number of linear subsystems. So the linear model based predictive control (MPC) technique is used for each subsystem. In the second one, the fuzzy model is considered as a nonlinear model of the system and the control signal is obtained by minimizing either the cumulative differences or the instant difference between set-point and fuzzy model output. The efficiency of these two fuzzy model predictive control (FMPC) approaches is demonstrated through two examples.

关键词： Predictive models Predictive control Mathematical model Equations Nonlinear systems control systems

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A discussion on Sugeno fuzzy logic approximations of nonlinear systems

A discussion on Sugeno fuzzy logic approximations of nonline...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Nabil Derbel Research Unit on Intelligent Control design &Optimisation of complex Systems (ICOS) National school of Engineers of Sfax (ENIS) University of Sfax Tunisia

This work is aimed at looking into the use of fuzzy systems for the study of nonlinear systems. In a first step, zero-order and first-order Sugeno fuzzy models are defined as approximators of nonlinear systems. It has been found that zero-order fuzzy systems are equivalent to the classical interpolation approach. Nonlinear terms have been limited by two fuzzy systems. The mean fuzzy system gives good accuracy. As illustrations, some numerical applications have been considered to show the efficiency of the use of fuzzy systems to study nonlinear problems.

关键词： Approximation methods Fuzzy systems Linear approximation Fuzzy control Nonlinear systems Differential equations Accuracy

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Some clustering techniques for modelling uncertain nonlinear systems

Some clustering techniques for modelling uncertain nonlinear...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Ali Zribi Mohamed Djemel Mohamed Chtourou Research Unit on Intelligent Control design & Optimisation of Complex Systems (ICOS) Department of Electrical Engineering ENIS Engineering School Sfax Tunisia

This paper presents popular unsupervised clustering algorithms based on neuro-fuzzy, fuzzy c-means (FCM) and agglomerative techniques. The purpose of this paper is to provide clustering methods able to cluster the data patterns without a priori information about the number of clusters. We will show that it is possible to reconcile the FCM algorithm with the unsupervised clustering algorithms. Finally, to show the efficiencies of these algorithms, we will apply them to model the behaviour of uncertain system.

关键词： Clustering algorithms Distance measurement Classification algorithms Support vector machine classification Partitioning algorithms Algorithm design and analysis Equations

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Forming Circle Formations of Multi-agent systems Under Actuator Faults 5th

Forming Circle Formations of Multi-agent Systems Under Actu...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Method of model's parameters classification using neural network for meat characterization

Method of model's parameters classification using neural net...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： M. Guermazi O. Kanoun N. Derbel Chair for Measurement and Sensor Technology Chemnitz University of Technology Reichenhainer Straße 70 09126 Chemnitz GERMANY Intelligent Control design & Optimization of complex Systems (ICOS) University of Sfax Sfax Engineering School Sfax TUNISIA Universite de Sfax Sfax TN Intelligent Control design & Optimization of complex Systems (ICOS) University of Sfax Sfax Engineering School BP W 1173-3038 TUNISIA

ISBN: (纸本)9781467364591

The main objective of this work is to develop the classification application for a new promising method for meat characterization getting information about the state of the vacuum packed meat in supermarket. A supervised training using neural networks and according to the back error propagation method is used. The training ensure a classification with high precision and with ability to answer correctly the inputs then with ability to classify the erroneous inputs which do not exist in the data base, without creating new classes. Method classification consist to classify the model parameters of the physical model of the meat according to a data base including the model's parameters for different beef muscle in different days.

关键词： Biomedical measurement Biology Phase measurement Biomembranes Impedance

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Fuzzy-Neural Networks for a piloted Quality Management System

Fuzzy-Neural Networks for a piloted Quality Management Syste...

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Mediterranean Electrotechnical Conference (MELECON)

作者： Hajer Ben Mahmoud Dammak Raouf Ketata Taieb Ben Romdhane Samir Ben Ahmed National Institute of Applied Science and Technology Tunis Tunisia Research units on Methods and tools for Complex Computer Systems (MOSIC) Tunis Tunisia Research units on Intelligent Control design and Optimization of Complex System (ICOS) Tunis Tunisia

The purpose of this paper is to provide a path for designing a tool for decision support to ensure the effectiveness of Quality Management System (QMS). For this, we propose a Fuzzy-Neural Networks (FNN) approach for improving the efficiency of such system. The aim of this approach is to classify the objectives for a real-world case study which presents a major problem for controlling the quality levels of its production lines. This approach provided a significant improvement when the testing data are various or complex.

关键词： Fuzzy neural networks Quality management Computational modeling Classification algorithms Biological system modeling Unified modeling language

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A New CMOS Current controlled Quadrature Oscillator Based on a MCCII

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Circuits and systems 2011年第4期2卷 269-273页

作者： Ashwek Ben Saied Samir Ben Salem Dorra Sellami Masmoudi Computor Imaging and Electronic Systems Group (CIEL) Research Unit on Intelligent Design and Control of complex Systems (ICOS) University of Sfax National Engineering School of Sfax (ENIS) Development Group in Electronics and Communications (EleCom)

In this paper, we propose a design of a current controlled Quadrature Sinusoidal Oscillator. The proposed circuit employs three optimized Multi-output translinear second generation current conveyer (MCCII). The oscillation condition and the oscillation frequency are independently controllable. The proposed Quadrature Oscillator frequency can be tuned in the range of [198 MHz –261 MHz] by a simple variation of a DC current. PSpice simulation results are performed using CMOS 0.35 μm process of AMS.

关键词： Quadrature Sinusoidal Oscillator Optimized MCCII

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Leader-follower based formation control of nonholonomic robots using the virtual vehicle approach

Leader-follower based formation control of nonholonomic robo...

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International Conference on Mechatronics (ICM)

作者： Jawhar Ghommam Hasan Mehrjerdi Maarouf Saad Research Unit on Intelligent Control and Optimization of Complex Systems National School of Engineer of Sfax ENIS Tunisia Department of Electrical Engineering École de technologie supérieure Québec Canada

In this paper we investigate the leader follower motion coordination of multiple nonholonomic mobile robots. A combination of the virtual vehicle and trajectory tracking approach is used to derive the formation architecture. A virtual vehicle is steered in such away it stabilizes to a shifted reference position/heading deflned by the leader, the velocity of the virtual vehicle is then provided for further use in designing control law for the follower independent from the measurement of leader's velocity. Position tracking control is then constructed for the follower to track the virtual vehicle using the backstepping and Lyapunov direct design technique. Simulations are provided to show the effectiveness of the proposed approach.

关键词： Lead Vehicles Robot kinematics

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