Title :
A robust neural adaptive force controller for a C5 parallel robot
Author :
Achili, B. ; Daachi, B. ; Ali-Cherif, A. ; Amirat, Y.
Author_Institution :
Comput. Sci. Lab., Univ. of Paris 8, St. Denis, France
Abstract :
In this paper, a neural adaptive force control of a parallel robot is proposed to solve the trajectory tracking problems. Assuming that the dynamic model of the system is a black box one, we use an a priori learning for its neural identification. And then, we use this results to design and adaptive control law. All adaptation laws of neural parameters are based on the stability of the closed loop system in the Lyapunov sense. This approach has been implemented on a C5 parallel robot, and the experimental results show the effectiveness of the proposed method.
Keywords :
Lyapunov methods; adaptive control; closed loop systems; force control; neurocontrollers; position control; robots; robust control; C5 parallel robot; Lyapunov stability; a priori learning; adaptation law; closed loop system; neural identification; neural parameter; robust neural adaptive force controller; trajectory tracking; Adaptive control; Force control; Parallel robots; Programmable control; Robust control; Adaptive Control; Artificial Neural Networks; Parallel Robots; Stability;
Conference_Titel :
Advanced Robotics, 2009. ICAR 2009. International Conference on
Conference_Location :
Munich
Print_ISBN :
978-1-4244-4855-5
Electronic_ISBN :
978-3-8396-0035-1
