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9th International Conference on Informatics in control, Automation and Robotics, ICINCO 2012

作者： Mtir, Ines Hadj Kaâniche, Khaled Vasseur, Pascal Chtourou, Mohamed Intelligent Control Design and Optimization of Complex Systems ENIS University of Sfax Sfax Tunisia Laboratoire D'Informatique du Traitement de L'Information et des Systèmes LITIS University of Rouen Rouen France

ISBN: (纸本)9789898565211

The objective of our system is to detect vehicles from aerial sequences. Theses sequences are taken from a camera mounted on UAV which flies over roads and highways. Our approach is to firstly compensate the motion introduced by the dynamic behaviour of the camera. This leads us to a problem of image registration. The moving regions (vehicles) are after that extracted using residual motion. The aim of this paper is to present a combined method for features matching and outliers rejection to increase the accuracy of the registration phase. We use first, the SIFT descriptors and then outliers are rejected using geometric constraints. This leads to a better registration and a minimum of false alarms in the detection phase.

关键词： Motion compensation

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Adaptive tracking control of a mobile manipulator

Adaptive tracking control of a mobile manipulator

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

作者： Amal Karray Moez Feki Research unit on Intelligent Control Sfax Engineering School Design & Optimization of complex Systems (lCOS) University of Sfax Sfax Tunisia

In this paper, we propose a computed torque controller for a dynamic model of nonholonomic mobile manipulator with bounded external disturbances in order to treat the adaptive tracking control. Firstly, a velocity controller is designed for the kinematic steering system. Secondly, a computed torque controller is designed such that the mobile manipulator velocity converges to the desired velocity controller deduced from the first step. In particular, the mobile manipulator can globally follow any path such as a straight line or a circle. Simulation results are given to demonstrate the effectiveness of the proposed controller.

关键词： TV Dynamics

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Breast cancer diagnosis using a hybrid evolutionary neural network classifier

Breast cancer diagnosis using a hybrid evolutionary neural n...

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Mediterranean Conference on control and Automation (MED)

作者： R. El hamdi M. Njah M. Chtourou Research unit on Intelligent Control design & Optimization of complex Systems (ICOS) Sfax Engineering School University of Sfax Sfax Tunisia

The important role that mammography is playing in breast cancer detection can be attributed largely to the technical improvements and dedication of radiologists to breast imaging. A lot of work is being done to ensure that these diagnosing steps are becoming smoother, faster and more accurate in classifying whether the abnormalities seen in mammogram images are benign or malignant. This paper takes a step in that direction by introducing a hybrid evolutionary neural network classifier (HENC) combining the evolutionary algorithm, which has a powerful global exploration capability, with gradient-based local search method, which can exploit the optimum offspring to develop a diagnostic aid that accurately differentiates malignant from benign pattern. The computational experiments show that the presented HENC approach can obtain better generalization and much lower computational cost than the existing methods reported recently in the literature using the widely accepted Wisconsin breast cancer diagnosis (WBCD) database with some improvements.

关键词： Artificial neural networks Training Classification algorithms Neurons Breast cancer Databases

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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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Multi objective optimization for piloting a Quality Management System: Study case

Multi objective optimization for piloting a Quality Manageme...

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2010 International Conference on System Science and Engineering, ICSSE 2010

作者： Mahmoud, H. Ben Ketata, R. Romdhane, T. Ben Ahmed, S. Ben Dept. of Physics and Instrwnentation Engineering INSAT: National Institute of Applied Science and Technology Tunis Tunisia Dept. of Physics and Instrwnentation Engineering ICOS: Research Unit on Intelligent Control Design and Optimization of Complex System Tunis Tunisia Dept. of Physics and Instrumentation Engineering MOSIC Research Unit on Methods and Tools for Complex Computer Systems Tunis Tunisia

ISBN: (纸本)9781424464746

This paper presents a decision support tool for the effectiveness of a Quality Management System (QMS) in a company. To develop this tool, a new approach PAHP based on the combination of the Pareto Optimality Concept (Poq and the Analytical Hierarchy Process (AHP). This approach is used to model and optimize the multi-objective function of real company which presents a major problem for controlling the quality level of production. © 2010 IEEE.

关键词： Multiobjective optimization

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Aerial sequence registration for vehicle detection

Aerial sequence registration for vehicle detection

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9th International Multi-Conference on systems, Signals and Devices, SSD 2012

作者： Mtir, Ines Hadj Kaâniche, Khaled Chtourou, Mohamed Vasseur, Pascal Intelligent Control Design and Optimization of Complex Systems ENIS University of Sfax Sfax Tunisia Laboratoire d'Informatique du Traitement de l'Information et des Systèmes LITIS Université de Rouen Rouen France

ISBN: (纸本)9781467315906

In this paper we present a system that aims at detecting and tracking moving objects from aerial video streams. These sequences are obtained from a camera mounted on an aerial vehicle which flies over roads and highways. In order to compensate the motion introduced by the dynamic behavior of the camera, we have to estimate geometrical transformations which stabilize consecutive frames. Our system is based on the use of Mutual Information as a criterion to find an affine model which relates a frame to a reference one. Then, moving regions are extracted using residual motion. The tracking module takes as input these regions to eliminate false alarms and to track vehicles all over the time. © 2012 IEEE.

关键词： Motion compensation

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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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Fuzzy identification of dynamic systems with adaptive structure

Fuzzy identification of dynamic systems with adaptive struct...

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

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

This paper deals with two approaches for on line structure identification of fuzzy models. In the first one, a constructive algorithm is adopted to generate the fuzzy rules: it starts with a single pattern and a single fuzzy rule and grows progressively to reduce the system error within the specified tolerance. In the second one, an evolutionary algorithm is applied based on an alternation between incremental and pruning criteria. Indeed, the rule base is expanded when the model can not reduce the system error and one rule is removed if it has a petty contribution in the model output along some patterns. The presented approaches have been applied for two examples of dynamic systems to compare the identification performance.

关键词： Mathematical model Training Adaptation model Evolution (biology) Equations Heuristic algorithms Artificial neural networks

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SYNCHRONIZATION OF GENERALIZED LORENZ SYSTEM USING ADAPTIVE controlLER

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IFAC Proceedings Volumes 2006年第8期39卷 2-6页

作者： Moez Feki Research unit on Intelligent Control design & Optimization of complex Systems (ICOS) Ecole Nationale d'Ingénieurs de Sfax BP W 3038Sfax Tunisia

This paper proposes a synchronization scheme for a class of continuous-time chaotic systems. We show that two systems belonging to the class of generalized Lorenz systems can be synchronized using an adaptive feedback controller. This controller is added to the response system to force a subset of its state variables to oscillate synchronously with their counterpart of the drive system. We show that the controller gain vector is tuned without any knowledge of the system model. To illustrate the efficiency of the proposed scheme, we present numerical simulations to synchronize two-by-two a Lorenz-like system, Chen system and Lü system.

关键词： Chaotic systems Chaotic synchronization Adaptive control Output regulation Lyapunov stability

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