Neural Network Adaptive Compensation Control of Free-Floating Space Robot

Abstract

Considering free-floating space robot in task space is a neural network adaptive control algorithm is proposed for trajectory tracking in this paper.The control scheme uses neural networks to approach the non-linearity model by establishing online model,and neural network approach errors and outside bounded disturbance can be eliminated by a robust controller.Parameters of system are distinguished by import GL matrix and multiplication Operator · into neural networks.The controller has no need of estimate value of inverse dynamic model and avoids the Jacobian matrix inverse operation.The control scheme can guarantee the stability of closed loop system and the asymptotic convergence of tracking errors based on the lyapunov theory.The simulation results show that the presented controller is effective in control accuracy and can satisfy request for real time,and has important value for engineering application.