سال انتشار: ۱۳۸۶

محل انتشار: اولین کنگره مشترک سیستم های فازی و سیستم های هوشمند

تعداد صفحات: ۶

نویسنده(ها):

Matineh Shaker – Control and Intelligent Processing Center of Excellence, Department of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
Caro Lucas – Control and Intelligent Processing Center of Excellence, Department of Electrical and Computer Engineering, University of Tehran, Tehran, Iran – Institute for Studies in Theoretical Physics and Mathematics, Tehran, Iran
Amir Homayoun Jafari – Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran.

چکیده:

This paper presents a neuro-fuzzy scheme for controlling rigid robot manipulators. The proposed control strategy consists of two modules. In first module, RBFN model from the dynamical equations of the plant is acquired to approximate the nonlinear relation between inputs and outputs of the system. In second step, after the neural model obtained, by assigning suitable membership functions, setting heuristic fuzzy rules, and applying gradient descentmethod for optimization, the fuzzy controller is obtained. Simulations performed on a two-link robot manipulator illustrate the methods and exhibit its performance. The results confirm the accuracy and robustness of controller.