Neural network adaptive robust attitude control of spacecraft

Abstract

A neural network adaptive robust controller for spacecraft attitude tracking is developed in this paper. The proposed controller achieves attitude tracking for a rigid spacecraft with a VSCMG cluster in the presence of parametric uncertainties and time-variation, taking into account dynamics of actuator and external disturbance. It is constructed by a nonlinear feedback compensator, a neural network estimator and a robust controller. The three-layered neural network is used to estimate and eliminate the unknown function with uncertain parameters. The robust controller is used to enhance the robustness of controller to approximate error and external disturbance. Lyapunov stability theory is considered to guarantee the stability of the closed-loop dynamics with the control law. As a result, the proposed controller ensures the uniform ultimate boundedness in tracking error and robustness to disturbance.