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Attack-compensated asynchronous output feedback control for stochastic switching systems with sojourn probability

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  • Mei, Xu
  • Cheng, Jun
  • Huang, Wentao

Abstract

This study addresses the problem of attack-compensated asynchronous output feedback control for stochastic switching systems with sojourn probability. Unlike traditional Markov/semi-Markov models that rely on transition probabilities, a novel switching rule is introduced that focuses on sojourn probability information associated with the target mode and sojourn time, which are easier to obtain than the well-known transition probabilities. Considering the vulnerability of stochastic switching systems to cyber-attacks, where the system state becomes unobservable and difficult to manage, a compensation-based output feedback controller framework is proposed. Using the Lyapunov method and stochastic analysis, sufficient conditions are provided to ensure system stability. Finally, the effectiveness and applicability of the developed approach are demonstrated using an F-404 aircraft engine system model.

Suggested Citation

  • Mei, Xu & Cheng, Jun & Huang, Wentao, 2025. "Attack-compensated asynchronous output feedback control for stochastic switching systems with sojourn probability," Applied Mathematics and Computation, Elsevier, vol. 485(C).
    • Handle: RePEc:eee:apmaco:v:485:y:2025:i:c:s0096300324004855
    DOI: 10.1016/j.amc.2024.129024
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    References listed on IDEAS

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    1. Haneen Badawi & Omar Abu Arqub & Nabil Shawagfeh, 2023. "Well-posedness and numerical simulations employing Legendre-shifted spectral approach for Caputo–Fabrizio fractional stochastic integrodifferential equations," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 34(06), pages 1-24, June.
    2. Haneen Badawi & Nabil Shawagfeh & Omar Abu Arqub & Kazem Nouri, 2022. "Fractional Conformable Stochastic Integrodifferential Equations: Existence, Uniqueness, and Numerical Simulations Utilizing the Shifted Legendre Spectral Collocation Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-21, November.
    3. Wang, Chen & Qi, Yiwen & Tang, Yiwen & Li, Xin & Ji, Ming, 2024. "Robust control with protected feedback information for switched systems under injection attacks," Applied Mathematics and Computation, Elsevier, vol. 475(C).
    4. Vijayakumar, M. & Sakthivel, R. & Kong, F. & Anthoni, S. Marshal, 2023. "Output tracking and disturbance rejection control for switched systems under asynchronous switching," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 211(C), pages 413-429.
    5. Wang, Yun & Fang, Tian & Kong, Qingkai & Li, Feng, 2024. "Zero-sum game-based optimal control for discrete-time Markov jump systems: A parallel off-policy Q-learning method," Applied Mathematics and Computation, Elsevier, vol. 467(C).
    6. Lucheng Sun & Tiejun Wu & Ya Zhang, 2023. "A defense strategy for false data injection attacks in multi-agent systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 54(16), pages 3071-3084, December.
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