Experimental study of robot manipulators based on robust adaptive control

Author

Chen, Wei-dong

Author_Institution

Inst. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao, China

Volume

2

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

976

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527085

Filename

1527085