Title :
Experimental study of robot manipulators based on robust adaptive control
Author_Institution :
Inst. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao, China
Abstract :
A radial basis function (RBF) network-based adaptive tracking control scheme is proposed for robot manipulators. A RBF network is used to generate control input signals that are similar to the control inputs of adaptive control using linear reparameterization of the robot manipulator. A sliding model control term is used to eliminate the effects of the network inherent approximation errors and external disturbance. The asymptotic stability of the control system is established using Lyapunov theorem. Experiments are given on a two-link robot in the end of paper, and validated the control arithmetic.
Keywords :
Lyapunov methods; adaptive control; asymptotic stability; manipulators; radial basis function networks; robust control; variable structure systems; Lyapunov theorem; asymptotic stability; control arithmetic; control input signals; linear reparameterization; radial basis function network-based adaptive tracking control scheme; robot manipulators; sliding model control; two-link robot; Adaptive control; Adaptive systems; Approximation error; Manipulators; Programmable control; Radial basis function networks; Robots; Robust control; Signal generators; Sliding mode control; RBF network; adaptive control; robot manipulators; sliding model control;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527085
