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Adaptive fault tolerant optimal control for high-order fully actuated system and its application in spacecraft attitude tracking using reinforcement learning

Author

Listed:
  • Wu, Xueqi
  • Sun, Wei

Abstract

This study addresses the adaptive optimal tracking problem for high-order fully actuated system (FAS). First, an optimal control strategy based on FAS theory and reinforcement learning (RL) is proposed, effectively solving the tracking problem within the actor-critic framework. Next, within the identifier-actor-critic framework, a sliding mode optimized control scheme for high-order FAS with actuator fault is introduced. Specifically, unlike existing fault-tolerant control results for high-order FAS, this method ensures trajectory tracking and performance optimization even in the presence of actuator faults, while avoiding the need for persistent excitation condition. Considering the strong robustness and rapid response advantages of sliding mode control (SMC), synchronous rapid tracking and optimal control of multiple variables are achieved by establishing a (n-1)-order sliding mode surface. Furthermore, rigorous theoretical analysis proves the boundedness of all signals within the closed-loop system. Finally, the effectiveness of the proposed control approaches are verified by a numerical simulation and a practical example of the spacecraft attitude system.

Suggested Citation

  • Wu, Xueqi & Sun, Wei, 2026. "Adaptive fault tolerant optimal control for high-order fully actuated system and its application in spacecraft attitude tracking using reinforcement learning," Applied Mathematics and Computation, Elsevier, vol. 512(C).
    • Handle: RePEc:eee:apmaco:v:512:y:2026:i:c:s0096300325004990
    DOI: 10.1016/j.amc.2025.129774
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    References listed on IDEAS

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    1. Li, Ze & Ren, Junchao, 2024. "Adaptive event-triggered non-fragile sliding mode control for uncertain T-S fuzzy singular systems with passive constraint," Applied Mathematics and Computation, Elsevier, vol. 472(C).
    2. Hu, Yinlong & Cai, Xuhao & Xu, Jin & Shi, Shang & Sun, Yonghui & Du, Haiping, 2024. "Analytical parameter tuning for a class of extended disturbance observers and sliding mode control," Applied Mathematics and Computation, Elsevier, vol. 469(C).
    3. Guan, Xinyu & Hu, Yanyan & Peng, Kaixiang, 2024. "Finite-time switching-like sliding mode fault-tolerant control for discrete-time cyber-physical systems under DoS attacks and intermittent faults," Applied Mathematics and Computation, Elsevier, vol. 469(C).
    4. Lixuan Zhang & Zhe Zhang & Huaiyuan Jiang, 2024. "Fully actuated system approach for high-order linear systems with high-order input derivatives," International Journal of Systems Science, Taylor & Francis Journals, vol. 55(12), pages 2506-2517, September.
    5. Bin Li & Xue Yang & Ranran Zhou & Guoxing Wen, 2022. "Reinforcement learning-based optimised control for a class of second-order nonlinear dynamic systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(15), pages 3154-3164, November.
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