Adaptive Neural Network Robust Control for Space Robot with Uncertainty
Abstract: The trajectory
tracking problems of a class of space robot manipulators with parameters and
non-parameters uncertainty are considered. An adaptive robust control algorithm
based on neural network is proposed by the paper. Neutral network is used to
adaptive learn and compensate the unknown system for parameters uncertainties,
the weight adaptive laws are designed by the paper, System stability base on
Lyapunov theory is analysised to ensure the convergence of the algorithm.
Non-parameters uncertainties are estimated and compensated by robust
controller. It is proven that the designed controller can guarantee the
asymptotic convergence of tracking error. The controller could guarantee good
robust and the stability of closed-loop system. The simulation results show
that the presented method is effective.
Author: Zhang Wenhui, Fang
Yamin, Ye Xiaoping
Journal Code: jptkomputergg130076