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共 131 条记录，以下是81-90 订阅

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DYNAMIC REDUNDANCY RESOLUTION FOR MOBILE MANIPULATORS USING POSITION FUZZY controlLER

DYNAMIC REDUNDANCY RESOLUTION FOR MOBILE MANIPULATORS USING ...

引用

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

作者： Boukattaya, M. Jallouli, M. Damak, T. Control of Industrial Process Unit Intelligent Control Design and Optimization of Complex Systems Unit Tunisia

ISBN: (纸本)9781424443451

In this paper, we present a dynamic redundancy resolution technique for mobile manipulators using a position fuzzy controller. First, the dynamic model of the mobile manipulator in feasible motion space is given. Next, a control algorithm is proposed which resolve the redundancy by decoupling the motion of the system into the end-effector motion in the task space and an internal motion in the null space and controls them in prioritized basis with priority given to the primary task. In order to achieve a good end-effector trajectory tracking, a position fuzzy controller is used to provide the torques needed to move the end-effector along the desired trajectory. Simulation results are given to illustrate the coordination of two subsystems in executing the desired trajectories.

关键词： mobile manipulators dynamic redundancy resolution fuzzy controller

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Dynamic redundancy resolution for mobile manipulators using position fuzzy controller

Dynamic redundancy resolution for mobile manipulators using ...

引用

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

作者： M. Boukattaya M. Jallouli T. Damak Control of Industrial Process Unit Tunisia Intelligent Control Design and Optimization of complex Systems Tunisia

关键词： Manipulator dynamics Fuzzy control control systems Motion control Torque control Robot kinematics Fuzzy systems Process control Electrical equipment industry Industrial control

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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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Optimal trajectory of a mobile robot by a Genetic design Fuzzy logic controller

Optimal trajectory of a mobile robot by a Genetic Design Fuz...

引用

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

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

Obstacle avoidance and path planning are the most important problems in mobile robots. Besides, finding methods for controlling and decreasing the real robot error in path have been another target for researchers investigation. Usual methods have two separated parts, research target and path planning with obstacle avoidance. In this context, a fuzzy logic controller has been constructed in order to train an intelligent robot. Genetic algorithms are used to optimize the consequences of a Sugeno fuzzy logic optimal controller for the mobile robot navigation. This is to search a target in an environment with and without obstacles. Simulation results verify successful applications of method for real motion situations. An application have been effected in the Khepera robot demonstrating. The Khepera robot can go to the goal and avoid the obstacles successfully.

关键词： Mobile robots Fuzzy logic Optimal control Genetic algorithms Virtual reality Navigation Wheels Path planning Robot control Motion control

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Robust and stable indirect fuzzy adaptive control for SISO nonlinear systems

Robust and stable indirect fuzzy adaptive control for SISO n...

引用

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

作者： D. Ben Halima M. Chtourou Research Unit on Intelligent Control design and Optimization of complex Systems (ICOS) National School of Engineers of Sfax Sfax Tunisia

An adaptive fuzzy controller is constructed from a collection of fuzzy IF-THEN rules whose parameters are changed or adapted according to adaptive laws for the purpose of controlling a nonlinear plant to track a reference trajectory. The fuzzy adaptive control is composed in two classes: direct and indirect one. The indirect fuzzy adaptive controller will be designed through two steps. The first one consists in the construction of a controller based on linguistic description about the unknown plant from human expert. To guaranty stability, a supervisory controller is added. The second step adjusts, on line, the parameters of the fuzzy controller based on the gradient descend. To ensure the robustness, fuzzy controller parameters are adjusted, on line, by a robust gradient descent method. Simulation results show the effectiveness of proposed algorithms in tracking of the inverse pendulum output.

关键词： Robust control Fuzzy control Fuzzy systems Adaptive control Nonlinear systems Programmable control Adaptive systems Trajectory Humans Stability

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

Decomposition and hierarchical control for discrete complex ...

引用

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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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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On the performances of neuronal classifiers for pattern recognition

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

引用

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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Robust fuzzy PID controller for discrete-time uncertain nonlinear systems

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

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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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