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

作者： Haifa Souilem Hassen Mekki Nabil Derbel Research unit on Intelligent Control design and Optimisation of complex Systems (ICOS) National School of Engineers of Sfax Sfax Tunisia National School of Engineers of Sousse National School of Engineers of Sfax Sfax Tunisia

This work is aimed at looking into the flatness control of the crane detailing adopted mechanisms and approaches in order to be able to control this system and to solve problems encountered during its functioning. The control objective is the sway free transportation of the crane s load taking the commands of the crane operator into account. Based on the mathematical model linearizing and stabilizing control laws for the slewing and luffing motion are derived using the input/output linearization approach. The method allows for transportation of the payload to a selected point and ensures minimisation of its swings when the motion is finished. To achieve this goal a mathematical model of the control system of the displacement of the payload has been constructed. A theory of control which ensures swing free stop of the payload is presented. Selected results of numerical simulations are shown. At the end of this work, a comparative study between the real moving and the desired one has been presented.

关键词： Cranes Trajectory Payloads Mathematical model Load modeling Pulleys

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Comparative study of voltage controlled current sources for biompedance measurements

Comparative study of voltage controlled current sources for ...

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

作者： Dhouha Bouchaala Qinghai Shi Xinyue Chen Olfa Kanoun Nabil Derbel Research unit of Intelligent Control design and Optimization of Complex Systems (ICOS) National School of Engineers of Sfax Sfax Tunisia Chair for Measurement and Sensor Technology (MST) Chemnitz University of Technology Chemnitz Germany

ISBN: (纸本)9781467315906

For bioimpedance measurement, the design of a voltage controlled current source (VCCS) is important to have a good compromise between performance of final results and patient safety. VCCS should have simultaneously large output impedance and wide bandwidth. In this paper, we compare between the Tietze topology, with and without Negative Capacitance Circuit (NCC), and the Improved Howland Current pump ICSA topology. Best results were reached with a Tietze current source with NCC over a wideband frequency range from 10 KHz to 1 MHz. The experiments show that the Tietze VCCS is able to drive loads of 25 Ω to 10 KΩ with current amplitude below 0.5 mA within the accuracy of 0.57% in practice. This fulfills even the requirements for bioimpedance measurements especially at high frequency and high load impedance.

关键词： Current measurement Bioimpedance Impedance Biomedical measurements Voltage measurement Topology Capacitance

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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-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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Face recognition under varying facial expression based on Perceived Facial Images and local feature matching

Face recognition under varying facial expression based on Pe...

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International Conference on Information Technology and e-Services (ICITeS)

作者： Hayet Boughrara Liming Chen Chokri Ben Amar Mohamed Chtourou Research unit on Intelligent Control design and Optimization of complex Systems (ICOS) Sfax Engineering School University of Sfax Tunisia Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS) CNRS Ecole Centrale Lyon (ECL) Université de Lyon France

Face recognition is becoming a difficult process because of the generally similar shapes of faces and because of the numerous variations between images of the same face. A face recognition system aims at recognizing a face in a manner that is as independent as possible of these image variations. Such variations make face recognition, on the basis of appearance, a difficult task. This paper attempts to overcome the variations of facial expression and proposes a biological vision-based facial description, namely Perceived Facial Images (PFIs), applied to facial images for 2D face recognition. Based on the intermediate facial description, SIFT-based feature matching is then carried out to calculate similarity measures between a given probe face and the gallery ones. Because the proposed biological vision-based facial description generates a PFI for each quantized gradient orientation of facial images, we further propose a weighted sum rule based fusion scheme. The proposed approach was tested on three facial expression databases: the Cohn and Kanade Facial Expression Database, the Japanese Female Facial Expression (JAFFE) Database and the FEEDTUM Database. The experimental results demonstrate the effectiveness of the proposed method.

关键词： Databases Face recognition Face Vectors Neurons Feature extraction Probes

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Robust Adaptive control for Mobile Manipulators

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International Journal of Automation and computing 2011年第1期8卷 8-13页

作者： Mohamed Boukattaya Tarak Damak Mohamed Jallouli Control of Industrial Process Unit National School of Engineers University of Sfax Intelligent Control Design and Optimization of Complex Systems Unit National School of Engineers University of Sfax

This paper addresses the trajectory tracking control of a nonholonomic wheeled mobile manipulator with parameter uncertainties and disturbances. The proposed algorithm adopts a robust adaptive control strategy where parametric uncertainties are compensated by adaptive update techniques and the disturbances are suppressed. A kinematic controller is first designed to make the robot follow a desired end-effector and platform trajectories in task space coordinates simultaneously. Then, an adaptive control scheme is proposed, which ensures that the trajectories are accurately tracked even in the presence of external disturbances and uncertainties. The system stability and the convergence of tracking errors to zero are rigorously proven using Lyapunov theory. Simulations results are given to illustrate the effectiveness of the proposed robust adaptive control law in comparison with a sliding mode controller.

关键词： Mobile manipulator trajectory tracking robust adaptive control sliding mode control uncertainties and disturbances.

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A new CMOS current controlled oscillator with minimum phase noise based on a low parasitic resistance CCII

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WSEAS Transactions on Circuits and systems 2011年第9期10卷 289-298页

作者： Ben Salem, Samir Ben Saïed, Achwek Masmoudi, Dorra Sellami Loulou, Mourad Laboratoire de l'Electronique et des Technologies de l'Information Tunisia Research Unit on Intelligent Design and Control of Complex Systems National Engineering School Sfax Tunisia

In this paper we present a design of a minimum phase noise current controlled oscillator in CMOS technology. Owing to their high degree of controllability, the second generation current conveyer is used as a basic block for our oscillator. Thus, the first step in our design was to improve static and dynamic behaviour of second generation current conveyers. We present therefore a design of CMOS class AB second generation current conveyors. The translinear implementation in CMOS technology was first studied and then a considerable improvement of the parasitic series resistance on port X is done by presenting a structure of CCII. With a control current of 300 mu;A, a reduction of RX by a factor of 10 is observed leading to a notable improvement of the frequency behaviour. This improved CCII version was used as a basic building block in the design of a new current controlled oscillator covering [100MHz-600MHz] frequency is presented. Phase noise characteristics of the presented oscillator are investigated. We present then a new methodology of modelling and optimisation of phase noise of current controlled oscillators for CMOS process. This optimization strategy leads to a minimum phase noise acting on device geometries and design sources. PSpice simulation results are performed using CMOS 0.35 mu;m process of AMS.

关键词： Phase noise

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Adaptive backstepping neural network approach to ship course control

Adaptive backstepping neural network approach to ship course...

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International Multi-Conference on systems, Signals and Devices

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

ISBN: (纸本)9781457704130

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. © 2011 IEEE.

关键词： Radial basis function 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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Adaptive Backstepping Neural Network approach to ship course control

Adaptive Backstepping Neural Network approach to ship course...

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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

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

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