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

作者： Yassine Bouteraa Jawhar Ghommam Research unit on Intelligent Control design & Optimization of complex Systems (ICOS) National Engineering School of Sfax (ENIS) Sfax Tunisia

This paper develops a new control approach to position synchronization of multiple robot manipulators based on emergent consensus algorithms. 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 control strategy is to stabilise position tracking of each manipulator while synchronizing its motion with other manipulator's position motion so that differential position errors amongst robots converge to zero. Simulations conducted on a multi-robots manipulators motion control system demonstrate the effectiveness of the method.

关键词： Robot control Robot kinematics Motion control Orbital robotics Manipulator dynamics control systems intelligent robots Communication system control Automatic control Production systems

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Synthesis of a fuzzy controller for the navigation of an electricwheelchair for handicapped

Synthesis of a fuzzy controller for the navigation of an ele...

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

作者： Malek Njah Mohamed Jallouli Research unit on Intelligent Control design & Optimization of complex Systems (ICOS) Sfax Engineering School University of Sfax Sfax Tunisia

Many researchers are interested in electric wheelchair automation because of the mobility problemsmet by a certain number of disabled and aged people. In this paper, we propose to associate a system's help navigation to a standard electric *** system is equipped with unit control and sensors to extract some *** elaborate a fuzzy controller which generates speed wheels orders in order to join the target position.

关键词： Fuzzy control Navigation Automatic generation control control systems control system synthesis Automatic control Wheelchairs Automation Aging Sensor systems

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IMC based automatic tuning method of PID controllers using neural networks

IMC based automatic tuning method of PID controllers using n...

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

作者： R. Chibani M. Chtourou Research Unit on Intelligent Control Optimization design & Optimization of Complex Systems (ICOS) Department of Electrical Engineering National Engineering School of Sfax (ENIS) Sfax Tunisia

In this paper, a new approach for neural PID tuning is presented based on the use of a neural network and the internal model control (IMC) principle. The neural network is used to adjust on line the PID controller after an off line training step. The developed approach is based on the use of a neural supervisor having as inputs the control signal, its correspondent output and the filter time constant and the PID parameters as outputs. The design of the supervisor is based on the procedures of linearization and IMC principle. We briefly outline the content of the tuning course and finish the paper with illustrative example where good performances have been obtained.

关键词： Three-term control Automatic control Neural networks Robust control Filters Robustness design optimization Lattices Filtering Reflection

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A constructive based hybrid training algorithm for feedforward neural networks

A constructive based hybrid training algorithm for feedforwa...

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

作者： Mounir Ben Nasr Mohamed Chtourou Research Unit on Intelligent Control Design & Optimization of Complex Systems (ICOS) Department of Electrical Engineering ENIS Engineering School Sfax Tunisia

This paper presents a new learning algorithm for feedforward neural networks. This algorithm uses the vigilance parameter to generate the hidden layer neurons. This process improves the initial weight problem and the adaptive neurons of the hidden layer. The proposed approach is based on combined unsupervised and supervised learning. In this algorithm, the weights between input and hidden layers are firstly adjusted by Kohonen algorithm with fuzzy neighborhood, whereas the weights connecting hidden and output layers are adjusted using gradient descent method. Two simulation examples are provided to demonstrate the efficiency of the approach compared with a number of other methods.

关键词： Neural networks Feedforward neural networks Neurons Fuzzy neural networks Vectors Organizing Euclidean distance Supervised learning Joining processes Learning systems

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Stability Analysis of Fuzzy Identification for Nonlinear Discrete systems - Part I: Theoretical Study

Stability Analysis of Fuzzy Identification for Nonlinear Dis...

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International Conference on Developments in esystems Engineering (DESE)

作者： Sonia Alimi Mohamed Chtourou Research unit on Intelligent Control design and Optimization of complex Systems (ICOS) Department of Electrical Engineering National School of Engineers of Sfax Sfax Tunisia

This paper presents the stability analysis of parameter identification. The Takagi Sugeno fuzzy model is employed to represent the discrete time nonlinear dynamical systems. Once the structure of the fuzzy model is fixed, the parameters can be optimized. The parameter identification is accomplished by applying the gradient method where the iteration rates are specific to each parameter. The stability of this algorithm is discussed by using two approaches which guarantee that the system is stable if the iteration rates satisfy sufficient conditions. The first approach deals with the consequence parameters and the second one deals with the premise parameters.

关键词： Stability analysis Fuzzy systems Parameter estimation design engineering Lyapunov method Linear matrix inequalities intelligent control design optimization Sufficient conditions Nonlinear systems

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A new scheme of signature extarction for iris authentication

A new scheme of signature extarction for iris authentication

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2009 6th International Multi-Conference on systems, Signals and Devices, SSD 2009

作者： Akrout, Belhassen Khanfir Kallel, Imen Benamar, Chokri Ben Amor, Boulbaba BP 1173 3038 Sfax Tunisia ICOS: Intelligent Control design Optimization of complex System Sfax Tunisia Telecomlille1: Telecom Lille1 Rue G. Marconi Cité Scientifique 59650 Villeneuve d'Ascq France

ISBN: (纸本)9781424443468

Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, thus is the most promising for high security environment. Iris recognition is proposed in this report. We describe some methods, the first one is based on grey level histogram to extract the pupil, the second is based on elliptic and parabolic HOUGH transformation to determinate the edge of iris, upper and lower eyelids, the third we used 2D Gabor Wavelets to encode the iris and finally we used the Hamming distance for authentication. ©2009 IEEE.

关键词： Hough transforms

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Robust sliding mode control applied to double Inverted pendulum system

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AIP Conference Proceedings 2009年第1期1107卷 222-228页

作者： Sonia Mahjoub Faiçal Mnif Nabil Derbel aResearch unit on Intelligent Control design & Optimization of complex Systems (ICOS) National engineering school of sfax BP W 3038 Sfax bDepartment of Electrical and Computer Engineering Sultan Qaboos University Muscat Oman

A three hierarchical sliding mode control is presented for a class of an underactuated system which can overcome the mismatched perturbations. The considered underactuated system is a double inverted pendulum (DIP), can be modeled by three subsystems. Such structure allows the construction of several designs of hierarchies for the controller. For all hierarchical designs, the asymptotic stability of every layer sliding mode surface and the sliding mode surface of subsystems are proved theoretically by Barbalat’s lemma. Simulation results show the validity of these methods.

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Decomposition and hierarchical control for discrete complex systems by fuzzy logic controllers

Decomposition and hierarchical control for discrete complex ...

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

作者： Najla Krichen Masmoudi Chokri Rekik Mohamed Djemel Nabil Derbel Research unit on Intelligent Control design and Optimisation of complex Systems (ICOS) Sfax Engineering School University of Sfax Sfax Tunisia

This paper proposes a method to compute sub-optimal control strategies of discrete time large-scale non-linear systems by fuzzy logic controllers. The method is based on the principle of decomposition of the global system into inter-connected subsystems. We consider that the non-linearities are located in the interconnections terms. Then, a mixed method of coordination procedure between different subsystems is formulated. So, for each subsystem, local optimal feedback gains are expressed as a function of the interconnection vector. Within this approach, first order Tkagi-Sugeno fuzzy logic systems have been constructed in order to identify these gains. Simulation results of a rotary crane show the effectiveness of the method and the robustness of the proposed approach.

关键词： control systems Fuzzy logic Large-scale systems Nonlinear control systems Vectors Cranes Fuzzy systems Space technology Optimal control intelligent control

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On the performances of neuronal classifiers for pattern recognition

On the performances of neuronal classifiers for pattern reco...

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

作者： Hayet Boughrara Mohamed Chtourou Research unit on Intelligent Control design and Optimisation of complex Systems (ICOS) Sfax Engineering School University of Sfax Sfax Tunisia

This work consists on the evaluation of the performances of three neural classifiers. The Multi-Layer Perceptron (MLP), the Self-Organizing Map (SOM), the Learning Vector Quantization (LV Q) are considered by this study. The example that will be considered in the evaluation of the technical classifications's performances is the handwritten character recognition.

关键词： Pattern recognition Character recognition Performance evaluation Multilayer perceptrons Vector quantization Data mining intelligent control Signal design design optimization design engineering

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Decomposition and hierarchical control for discrete large scale system using neural networks

Decomposition and hierarchical control for discrete large sc...

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International Conference on Advances in Computational Tools for Engineering Applications, ACTEA

作者： Najla Krichen Masmoudi Chokri Rekik Mohamed Djemel Nabil Derbel Research Unit on Intelligent Control design and Optimisation of complex Systems (ICOS) Sfax Engineering School University of Sfax Sfax Tunisia

This paper presents a method to compute sub-optimal control strategies of discrete time large scale nonlinear systems by neural networks. The method is based on the principle of decomposition of the global system into interconnected subsystems for which we consider that non-linearities are located in the interconnection terms. Then, a mixed method is considered to coordinate between different subsystems in order to compute the optimal control. So, for each subsystem, local optimal feedback gains are expressed in terms of the interconnection vector. For this purpose, neural networks have been used in order to identify these gains. Simulation results of a rotary crane show that the proposed method yields to satisfactory performances. The robustness of the proposed approach is analysed.

关键词： control systems Large-scale systems Neural networks Computer networks Nonlinear control systems Nonlinear systems Optimal control Neurofeedback Computational modeling Cranes

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