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: jptkomputergg130079
