Adaptive Control of Satellite Attitude Tracking Based on RBF Neural Network

Abstract

Aiming at the problem of satellite attitude tracking with uncertain moment of inertia and external interference, an adaptive control method based on RBF neural network is proposed. First, based on the error quaternion and error angular velocity, the kinematics and dynamics equations of satellite attitude tracking are derived. Then, a direct controller based on RBF neural network is designed, and the Lyapunov stability theory is used to prove that the designed controller can ensure the progressive stability of the satellite attitude tracking system. Finally, the simulation of the designed control method was verified by MATLAB/SIMULINK software. The results show that the adaptive control based on RBF neural network can effectively overcome the influence of uncertain disturbances in the system, improve the accuracy of attitude control, and has a strong Robustness.