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检索条件"机构=Intelligent Control Design and Optimization of Complex Systems Unit"

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Track following problem of a VCM actuator servo system for hard disc drives using predictive control

Track following problem of a VCM actuator servo system for h...

引用

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

作者： M. Taktak Meziou J. Ghommam N. Derbel Intelligent Control Design and Optimization of Complex Systems Unit National Engineering School of Sfax Tunisia

This paper describes a Predictive control method used for track following control in hard disc drives (HDD). While reading/writing data, the head must be positioned on the target data track quickly and precisely, and with the predictive control, we have achieved good tracking with the suppression of vibrations from high-order resonance modes. Simulation results show the effectiveness of the proposed approach and the servo system with predictive control presents good performances.

关键词： Actuators Predictive control Hard disks Cost function Target tracking Mathematical model Frequency response

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Adaptive Backstepping Neural Network approach to ship course control

Adaptive Backstepping Neural Network approach to ship course...

引用

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

作者： M. Taktak Meziou J. Ghommam N. Derbel Intelligent Control Design and Optimization of Complex Systems Unit National Engineering School of Sfax Tunisia

This paper describes an Adaptive Backstepping Neural Network (ABNN) method used for a ship course tracking control. The ship model is described by a third order nonlinear model whose parameters are unknown. The control design uses estimate values of unknown parameters of the system. Then, adaptive laws of the estimation of these values have been proposed. The stability of the controlled system has been ensured by the use of a Lyapunov function. Simulation results show the effectiveness of the proposed approach and the designed controller can be applied to the ship course tracking with good performances.

关键词： Artificial neural networks Marine vehicles Backstepping Lyapunov methods Equations Convergence Adaptation model

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Fuzzy predictive control based on Takagi-Sugeno model for nonlinear systems

Fuzzy predictive control based on Takagi-Sugeno model for no...

引用

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

作者： Latifa Dalhoumi Mohamed Djemel Mohamed Chtourou Research unit of Intelligent Control Design and Optimization of Complex Systems National School of Engineering Sfax Tunisia

In this paper, a method of designing a nonlinear predictive controller based on a fuzzy model of the system is presented. The Takagi-Sugeno fuzzy model is used as a powerful structure for representing nonlinear dynamic systems. So, the strategy of the fuzzy predictive control based on a fuzzy Takagi-Sugeno model is applied to the control of a chemical reactor. Indeed, the work is consists to develop, in a first step, a fuzzy model from a merger of a number of local models obtained by the principle of linearization around an operating point, or by learning through the gradient algorithm. In a second stage and basis on local models already developed, a fuzzy predictive control is synthesized with different approaches. The principal aim is to apply local generalized predictive control.

关键词： Mathematical model Predictive models Computational modeling Argon Equations Nonlinear systems Takagi-Sugeno model

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Neural approaches for modelling nonlinear systems

Neural approaches for modelling nonlinear systems

引用

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

作者： Amina Turki Mohamed Chtourou Mohamed Djemel Research unit of Intelligent Control Design and Optimization of Complex Systems National School of Engineering Sfax Tunisia

This paper deals with the problem of neural modeling of nonlinear systems. In a first place, we will discuss the neural modeling process. The approach adopted of neural modeling will be presented in a second place; this method is based on mono-network neural modeling and multi-network neural modeling. The results of simulation obtained will be illustrated by a nonlinear system of second order and by a chemical process.

关键词： US Department of Energy

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A Multi Objective Genetic Algorithm based optimization of wavelet transform implementation

A Multi Objective Genetic Algorithm based optimization of wa...

引用

International design and Test Workshop

作者： S. Fakhfakh Ghribi D. Sellami Masmoudi N. Derbel Research unit on Intelligent Control design and Optimization of complex Systems (lCOS) University of Sfax Sfax Tunisia

In this paper, an optimization method based on multi objective genetic algorithm (MOGA) is proposed in the design of a filter bank discrete wavelet transform (DWT). The different criteria are related to wavelet perfect reconstruction condition and minimization of the total number of non zero bits. Simulation results illustrate the optimization process applied to a case study : the Biorthogonal 9/7 DWT. They reveal improvement of compression performance and minimization of the number of non-zero bits. Performance measurements of the introduced method are even better than the original unquantized filter itself. Implementation results show a reducing hardware cost in comparison of proposed quantization method with trivial ones.

关键词： Genetic algorithms Wavelet transforms Discrete wavelet transforms optimization methods Algorithm design and analysis Filter bank Measurement Hardware Costs Quantization

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Modular ultrasonic sensor platform for mobile robot

Modular ultrasonic sensor platform for mobile robot

引用

International Conference on Renewable Energies and Vehicular Technology (REVET)

作者： Imen Maâlej Mohamed Ouali Nabil Derbel ENIS Research Unit on Intelligent Control design & Optimisation of complex Systems (ICOS) University of Sfax Tunisia Computer and Embedded Systems Algeria ICOS: Research Unit on Intelligent Control Design and Optimization of Complex System Tunisia

The ultrasonic sensor is the most replied sensor in mobile robot to get environmental information and avoid obstacles. In fact, this type of sensors offers satisfactory results with affordable cost. However, one sensor is insufficient for a better perception of the environment. In this paper we opt for the conception of an ultrasonic sensor network to extract as much information as possible for measuring the distance between the robot and the obstacle. The algorithm for distance calculation is based on the measurement of the time of flight for the ultrasonic wave. The experimental results show a good performance of the conceived system for the distinction between different shapes of obstacles.

关键词： Acoustics Robot sensing systems Microcontrollers Shape Ultrasonic variables measurement Transmitters Shape measurement

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Hardware implementation of pulse mode RBFNN based edge detection system on virtex V platform

Hardware implementation of pulse mode RBFNN based edge detec...

引用

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

作者： Amir Gargouri Mohamed Krid Dorra Sellami Masmoudi Research unit of Intelligent Control design and Optimization of complex Systems (ICOS) National School of Engineering Sfax Tunisia

In this paper, we have proposed a new architecture of RBFNN. Neural network efficiency in embedded systems offers the possibility of reconfiguration and the genericity of the solution. Indeed, the same integrated system can approximate any input-output function thanks to the parameters update on the chip. RBF neural networks constitute a subset of the neuronal networks, which has a great potential in reducing the size of the network. Pulse mode neural networks reduce significantly hardware resources by replacing the conventional huge multiplier by a simple frequency multiplier. As application, we approximate with the proposed RBF network, a Canny operator based edge detection, which is an important step in image processing. Acceptable edge detection approximation was done, with a mean generalization error of (4,604 %) on the Wang image database. Moreover, a design synthesis on FPGA virtex V platform was done, the results of implementation lead to an operating frequency of 445,295 MHz, which offers real time application performances.

关键词： Image edge detection Artificial neural networks Training Radial basis function networks Neurons Simulation Hardware

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design of optimal fuzzy logic controller with genetic algorithms

Design of optimal fuzzy logic controller with genetic algori...

引用

IEEE International Symposium on intelligent control (ISIC)

作者： C. Rekik M. Djemel N. Derbel A. Alimi Research unit on Intelligent Control Design and Optimization of complex Systems Tunisia Research Group on Intelligent Machines REGIM University of Sfax Tunisia

This paper looks into the determination of optimal trajectories of a nonlinear model of a two-link articulated manipulator. In a first step, genetic algorithms are used to generate an optimal control sequence which is used to bring the manipulator robot into a desired position. In a second step, genetic algorithms optimize the parameters of membership functions to facilitate the realization of a Sugeno fuzzy logic based optimal controller. Simulation results show that the second step gives suboptimal solutions, however the first step yields to optimal solutions which are very sensitive with respect to the parameter variation of the system.

关键词： Algorithm design and analysis Fuzzy logic Optimal control Genetic algorithms optimization methods control systems Manipulators Fuzzy control Robot sensing systems Fuzzy neural networks

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Classification of rotor fault in induction machine using Artificial Neural Networks

Classification of rotor fault in induction machine using Art...

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

作者： Aida Drira Nabil Derbel Research unit on Intelligent Control design & Optimization of complex Systems (ICOS) Engineering School of Sfax (ENIS) Sfax Tunisia

In this paper, we have developed a feedforward neural networks to detect and to diagnosis rotor fault on induction motors using stator currents. In the first step, causes and effects of rotor fault have been studied, particularly, the number of broken bars has been considered. Then, in the second step, the number of broken rotor bars has been localized by Artificial Neural Networks (ANN), using the Fast Fourier Transform. Simulation results show that the Neural Network proposed approach presents a good tools for the diagnostic of induction machines.

关键词： Rotors Artificial neural networks Bars Stators Neurons Induction motors Circuit faults

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controllability analysis of 1-DOF linear juggling system

Controllability analysis of 1-DOF linear juggling system

引用

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

作者： Behij Ben Amor Nehla Kraief Haded Faical Mnif Research unit on Intelligent Control design & Optimization of complex Systems (ICOS) Sfax Tunisia Sultan Qaboos University Oman

The paper deals with the controllability study of a subclass of juggling systems, named linear juggler. It comes that despite the simple representation of such systems, their controllability is in general not easy to establish, since they remain highly nonlinear dynamical systems. In this paper we are interested in the controllability properties of one degree of freedom linear juggling system.

关键词： controllability control system analysis Manipulator dynamics Robots Mechanical systems Nonlinear dynamical systems Nonlinear systems Signal analysis intelligent control Signal design

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