Predefined-Time Fault-Tolerant Control of Rigid Spacecraft With Prescribed Performance

Abstract

This paper proposes a predefined-time fault-tolerant control strategy to address the attitude tracking problem of rigid spacecraft, considering time-varying actuator faults, inertia uncertainties and unknown external disturbances. To ensure both transient and steady-state performance of attitude tracking, prescribed performance functions are introduced, and coordinate transformations are employed to convert constrained tracking errors into unconstrained states. Based on the transformed errors and the command-filtered backstepping recursive design procedure, a predefined-time fault-tolerant controller incorporating radial basis function neural networks (RBFNNs) is systematically developed. RBFNNs are utilized for online estimation and compensation of the system's unknown dynamics, thereby improving control accuracy. The proposed controller guarantees that spacecraft attitude errors converge to minimal neighbourhoods of the origin within a predefined settling time. Finally, comparative simulation results validate the effectiveness of the proposed control approach.