关键词: 神经网络, 不确定性, 空间机器人, 整体逼近, 自适应控制

Abstract: Considering trajectory tracking of a class of free-floating space robot with disturbance and model uncertainties, a neural network adaptive control strategy which based on the global model approximation is proposed for space robot. The control strategy uses neural networks to approach the uncertain model under uncertain gravity environment by global approximation, adjust learning the uncertain part of system on-line. The neural network approach errors and outside bounded disturbance can be eliminated by a robust controller. The control strategy can not depend on the model, simplifies the structure of control system, and can be used under uncertain gravity environment by the same controller. The control strategy can guarantee the stability of system and the asymptotic convergence of tracking errors based on the Lyapunov theory. The simulation result that this control strategy under uncertain gravity environment is effective.

Key words: neural network, uncertainty, space robot, global approximation, adaptive control