Adaptive fault-tolerant control for spacecraft attitude systems with fixed-time convergence

This paper proposes a backstepping fixed-time control method, which is designed for the spacecraft attitude tracking control system considering external disturbances and actuator faults. By introducing a radial basis function neural network (RBFNN), the proposed method can enhance the whole performance of the controller. First, the controller is formulated by designing the virtual control inputs and the fixed-time command filter. Based on backstepping method and RBFNN, a fault-tolerant attitude control law for a rigid spacecraft system is established and giving a fixed-time control law for stabilizing the spacecraft attitude. Then, the attitude tracking error and the angular velocity error converge in a fixed-time is proved to be stability by the Lyapunov theorem. Finally, numerical simulations are provided to verify the effectiveness of the proposed theoretical results.