Robust control of free-floating space robot based on neural network

The trajectory tracking of a class of free-floating space robot manipulators with disturbance and model parameter uncertainties is considered. An adaptive robust control algorithm based on neural network is proposed. The state sections of a neural network are compartmentalized. It is used to adaptive learn and compensate the unknown system by syncretize with sliding model variable structure controller, and approach errors as disturbance are eliminated by a robust controller. The robust controller based on H_∞ theory and weight adaptive laws on-line based on Lyapunov are obtained. Above these assure the stability of the whole system, and L2 gain is also less than the index. The control scheme possesses great control accuracy and dynamic function. The simulation results show that the presented adaptive robust control algorithm based on neural network is effective.