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Dynamic event-triggered asynchronous fault detection for Markov jump systems with partially accessible hidden information and subject to aperiodic DoS attacks

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  • Liu, Mengmeng
  • Yu, Jinyong
  • Liu, Yu

Abstract

This paper is concerned with the event-triggered asynchronous fault detection (FD) problem for Markov jump systems with partially accessible hidden information and subject to aperiodic denial-of-service (DoS) attacks. The hidden Markov model with partially unknown probabilities is introduced to characterize the asynchronous phenomenon between the system and the filter, where the partially unknown probabilities may exist in the transition rate matrix of Markov chain, the conditional probability matrix of detected signal, or in both of them. In order to save the limited network bandwidth while resisting the aperiodic DoS jamming attacks, a new resilient dynamic event-triggered communication strategy is devised. Then, a new switched residual model for asynchronous FD is formulated by comprehensively considering the effects of the event-triggered scheme, asynchronization, and DoS attacks. By means of this model combined with the piecewise stochastic Lyapunov-Krasovskii functional approach, sufficient conditions are derived to guarantee the stochastic stability of the resulting switched residual system with desired dissipativity performance. Based on convex optimization techniques, an explicit expression of the desired asynchronous FD filter is derived. Finally, a single-link robot arm and a mass-spring system model are utilized to demonstrate the effectiveness of the proposed design technique.

Suggested Citation

  • Liu, Mengmeng & Yu, Jinyong & Liu, Yu, 2022. "Dynamic event-triggered asynchronous fault detection for Markov jump systems with partially accessible hidden information and subject to aperiodic DoS attacks," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    • Handle: RePEc:eee:apmaco:v:431:y:2022:i:c:s0096300322003915
    DOI: 10.1016/j.amc.2022.127317
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    References listed on IDEAS

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    1. Xing, Mingqi & Wang, Yanqian & Zhuang, Guangming & Chen, Fu, 2021. "Event-based asynchronous and resilient filtering for singular Markov jump LPV systems against deception attacks," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    2. Liu, Xuan & Zhai, Ding & He, Da-Kuo & Chang, Xiao-Heng, 2018. "Simultaneous fault detection and control for continuous-time Markovian jump systems with partially unknown transition probabilities," Applied Mathematics and Computation, Elsevier, vol. 337(C), pages 469-486.
    3. Zeng, Pengyu & Deng, Feiqi & Gao, Xiaobin & Liu, Xiaohua, 2021. "Sampled-data resilient H∞ control for networked stochastic systems subject to multiple attacks," Applied Mathematics and Computation, Elsevier, vol. 405(C).
    4. Li, Qiang & Liang, Jinling, 2022. "Non-fragile asynchronous state estimation for Markovian switching CVNs with partly accessible mode detection: The discrete-time case," Applied Mathematics and Computation, Elsevier, vol. 412(C).
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    Cited by:

    1. Li, Xin & Mu, Xiaowu, 2024. "Dynamic event-triggered fuzzy control for nonlinear singular semi-Markovian jump systems via state decomposition approach," Applied Mathematics and Computation, Elsevier, vol. 466(C).

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