Spacecraft attitude fault-tolerant stabilization against loss of actuator Effectiveness: A novel iterative learning sliding mode approach

• Published in: Advances in space research Vol. 72; no. 2; pp. 529 - 540
• Main Authors: Jia, Qingxian, Ma, Rui, Zhang, Chengxi, Varatharajoo, Renuganth
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.07.2023
• Subjects: Fault reconstruction; Fault-tolerant control; Iterative Learning observer; Iterative Learning sliding mode control; Spacecraft attitude control; Spacecraft attitude control; Iterative Learning observer; Fault reconstruction; Iterative Learning sliding mode control; Fault-tolerant control
• ISSN: 0273-1177; 1879-1948
• DOI: 10.1016/j.asr.2023.02.041

This paper investigates the attitude fault-tolerant stabilization problem for a spacecraft subjected to its actuator effectiveness loss, inertia uncertainties and space disturbances. A novel Iterative Learning Sliding Mode Observer (ILSMO) is proposed to reconstruct the actuator effectiveness factors robustly and accurately by combining the P-type iterative learning algorithm with the sliding mode approach. Based on the reconstructed fault signals, an Iterative Learning Sliding Mode Controller (ILSMC) is designed to guarantee the closed-loop spacecraft attitude fault-tolerant stabilization by compensating for its lumped disturbance. The ILSMO and ILSMC stabilities are guaranteed using the Lyapunov direct approach, respectively. Finally, the numerical simulation results show that the proposed ILSMO-ILSMC-based spacecraft attitude fault-tolerant stabilization method is effective and superior.