Design of Robust Intelligent Controller for Space Robot in Task Space

Abstract

The problem of tracking control of free-floating space robot based on neural network in task space was studied in this paper.A RBF neural network was used to approximate the highly nonlinear model of freefloating space robot and a robust controller was designed to compress the approximation errors and external disturbances.New on-line adaptation laws of parameters and weights of RBF neural network were proposed using Lyapunov direct method.The robust controller was proposed based on dissipative theory.Above these assured the stability of the whole system,and L2 gain also was less than the index.Simulation results of a two-link planar free-floating space robot verify the validity of the proposed robust intelligent controller in the presence of uncertainties and disturbances.