Control Input Saturation Sliding-Mode Control System Design for Spacecraft Based on Neural Network

For spacecraft tracking system, the input control is saturated because of the actuators constrains. In this paper, the spacecraft single shaft motion is considered and a sliding-mode control system under control input saturation has been investigated. Theory proves that this method can ensure the stability of system and implement effective control under control input saturation. Furthermore, the regulating function of neural network can estimates the control input error caused by saturation, and there is a certain external interference, the RBF neural network can ensure strong robustness of the system. Simulation results show that the proposed sliding-mode control system has strong ability of estimation error and better dynamic performance under control input saturation.