Adaptive Attitude Control Using Neural Network Observer Disturbance Compensation Technique

In this paper, the problem of spacecraft attitude control using adaptive neural network disturbance compensation technique is investigated. The proposed disturbance observer is developed based on the Radial Basis Function (RBF) neural network. Firstly, the RBF neural network algorithm and spacecraft dynamic model are given. Then, the RBF neural network observer is developed to estimate the external disturbance moment. Using the estimated information, an adaptive neural network disturbance compensation controller is designed. Meanwhile, the stability of closed-loop attitude control system is analyzed by using Lyapunov approach. The simulation results show that compared with the traditional PD controller, the developed control scheme can decrease the effect of the external disturbance and has a better control performance.