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检索条件"机构=ICOS: Research Unit on Intelligent Control"

共 57 条记录，以下是31-40 订阅

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Integrated genetic algorithms and fuzzy control approach for optimization mobile robot navigation

Integrated genetic algorithms and fuzzy control approach for...

引用

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

作者： Chokri Rekik Mohamed Jallouli Nabil Derbel Research unit on Intelligent Control design & Optimization of complex Systems (ICOS) Sfax Engineering School University of Sfax Sfax Tunisia

This paper presents an optimal fuzzy logic controller design using optimization techniques. The fuzzy logic controller (FLC) has been developed and implemented for the motion of the robot from an initial position towards another desired position, taking into account the kinematic constraints. First, we have carried out a simulation of a fuzzy logic based controller which determines the speed values of each driving wheel, while seeking the goal. Secondly, an optimization of this controller has been realized using gradient method and genetic algorithms. A comparison between these methods has been effected. Not only simulation results are shown in this paper, but the ldquoreal-timerdquo implementation has been realized onto the mini robot Khepera II. Simulation results verify successfully the application of the proposed method to real motion situations.

关键词： Genetic algorithms Fuzzy control Mobile robots Navigation Fuzzy logic Optimal control Design optimization Motion control Kinematics Wheels

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Robust fuzzy PID controller for discrete-time uncertain nonlinear systems

Robust fuzzy PID controller for discrete-time uncertain nonl...

引用

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

作者： Amira Aydi Imen Zaidi Mohamed Djemel Mohamed Chtourou Research unit of Intelligent Control design and Optimization of complex Systems (ICOS) National Engineering School of Sfax (ENIS) Sfax Tunisia

This paper presents a design method of robust fuzzy PID controller for discrete-time uncertain nonlinear systems. The Takagi-Sugeno fuzzy model with parameter uncertainties is employed to describe discrete-time uncertain nonlinear system with bounded uncertainties. A robust pole placement called pole coloring is used to control each local model. controller parameters are determined through cost function minimization by an optimization procedure. Closed-loop system's poles are chosen according to desired performance. The global controller is obtained by local control inference. Finally, two examples are treated to illustrate the effectiveness of the proposed design method.

关键词： Robust control Fuzzy control Fuzzy systems Three-term control Nonlinear control systems control systems Nonlinear systems Design methodology Takagi-Sugeno model Uncertain systems

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Synchronization control of multiple robots manipulators

Synchronization control of multiple robots manipulators

引用

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

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

引用

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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A constructive based hybrid training algorithm for feedforward neural networks

A constructive based hybrid training algorithm for feedforwa...

引用

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...

引用

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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IMC based automatic tuning method of PID controllers using neural networks

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

引用

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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intelligent model of continuous improvement mechanisms scope of QMS

Intelligent model of continuous improvement mechanisms scope...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Sofiene Hermi Taieb Ben Romdhane Raouf Ketata Department of Physics and Instrumentation Engineering National Institute of Applied Science and Technology Tunis Tunisia Research Unit on Intelligent Control Design and Optimization of Complex System (ICOS) National Engineering School of Sfax Sfax Tunisia

This work proposes a new methodology to evaluate and improve the QMS (Quality Management System) effectiveness and efficiency to succeed for a factual approach including all monitoring parameters. This idea is justified by the difficulties incurred by the organizations to establish a continuous improvement's system based on the objectives and the process approach. In addition, the guidelines defined by the FDX 50-174 part published by AFNOR to assess the QMS effectiveness, still guides defining the assessment criteria and progress levels. Indeed, to facilitate the continuous improvement system's integration, we propose a new methodology based on a broad range of monitoring tools (functional and operational indicators, audits, quality control, customer satisfaction) and including the requirements of the process and the system approach.

关键词： Continuous improvement Design engineering Quality management Condition monitoring Customer satisfaction ISO standards Physics Instruments Management training Cybernetics

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A DISCUSSION ON SUGENO FUZZY LOGIC APPROXIMATIONS OF NONLINEAR SYSTEMS

A DISCUSSION ON SUGENO FUZZY LOGIC APPROXIMATIONS OF NONLINE...

引用

5th International Multi-Conference on Systems, Signals and Devices

作者： Derbel, Nabil Research Unit on Intelligent Control Design and Optimisation of Complex Systems (ICOS) University of Sfax National School of Engineers of Sfax (ENIS)

ISBN: (纸本)9781424422050

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： Nonlinear Problems Zero-Order Sugeno Fuzzy Systems First-Order Sugeno Fuzzy Systems Nonlinear Approximators

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