Title :
Neural sliding mode controller of uncertain robot manipulators using H∞ method
Author :
Chen, Weidong ; Tang, Dezhi ; Wang, Hongrui ; Chen, Li
Author_Institution :
Dept. of Inf. Eng., Yanshan Univ., Qinhuangdao, China
Abstract :
An adaptive neural robust controller based on H∞ method is presented for trajectory of uncertain robot manipulators. An RBF neural network is used to compensate the plant parameter uncertainties, in addition, sliding-mode control action is included to eliminate the effect of approximation error via neural network approximation and the H∞ tracking performance ensures the robust stability that under a prescribed attenuation level for external disturbance. The simulation shows that the control law can guarantee fast convergence of trajectory tracking error as well as robustness for parameter uncertainties and external disturbances.
Keywords :
H∞ control; adaptive control; control engineering computing; manipulators; neurocontrollers; radial basis function networks; stability; uncertain systems; variable structure systems; H∞ method; RBF neural network; adaptive neural robust controller; neural sliding mode control; parameter uncertainties; robot manipulators; robust stability; Adaptive control; Approximation error; Manipulators; Neural networks; Programmable control; Robot control; Robust control; Robust stability; Sliding mode control; Uncertain systems;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1343671
