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Event-based asynchronous and resilient filtering for singular Markov jump LPV systems against deception attacks

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  • Xing, Mingqi
  • Wang, Yanqian
  • Zhuang, Guangming
  • Chen, Fu

Abstract

This article addresses the issue of dissipative asynchronous and resilient filter design for singular Markov jump linear parameter-varying (SMJLPV) systems against deception attacks under the dynamic event-triggered transmission protocol. Firstly, an improved dynamic event-triggered transmission protocol is provided to further relieve the channel congestion caused by the bandwidth limited communication network. Then, the deception attack, which can potentially destroy the integrity of the system, is modelled as a random variable satisfying Bernoulli distribution. Since the filter cannot identify the original system mode accurately, the hidden-Markov-model (HMM) is established to describe the phenomenon that two modes are out of synchronization. By augmenting the states of the original system and the filter, the filtering error systems are converted into SMJLPV systems with partially known transition rates (TRs). Based on the parameter-dependent linear matrix inequalities (PDLMIs), a cooperative design technique for the asynchronous filter and the weighting matrix of the dynamic event-triggered transmission protocol is proposed. Lastly, a numerical instance and a resistance-inductance-capacitance (RLC) switch circuit system are employed to verify the effectiveness of the theoretical results.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:apmaco:v:403:y:2021:i:c:s0096300321002666
    DOI: 10.1016/j.amc.2021.126176
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    References listed on IDEAS

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    1. Zhao, Nan-Nan & Wu, Li-Bing & Ouyang, Xin-Yu & Yan, Yan & Zhang, Rui-Yan, 2019. "Finite-time adaptive fuzzy tracking control for nonlinear systems with disturbances and dead-zone nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    2. Wang, Yanqian & Chen, Fu & Zhuang, Guangming & Yang, Guang, 2020. "Dynamic event-based mixed H∞ and dissipative asynchronous control for Markov jump singularly perturbed systems," Applied Mathematics and Computation, Elsevier, vol. 386(C).
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    Cited by:

    1. Zhu, Zhibin & Wang, Fuyong & Yin, Yanhui & Liu, Zhongxin & Chen, Zengqiang, 2022. "Distributed fault-tolerant containment control for a class of non-linear multi-agent systems via event-triggered mechanism," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    2. Oliveira, Pedro M. & Palma, Jonathan M. & Lacerda, Márcio J., 2022. "H2 state-feedback control for discrete-time cyber-physical uncertain systems under DoS attacks," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    3. Xu, Qiyi & Zhang, Ning & Qi, Wenhai, 2023. "Finite-time control for discrete-time nonlinear Markov switching LPV systems with DoS attacks," Applied Mathematics and Computation, Elsevier, vol. 443(C).
    4. 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).
    5. Zhu, Laixiang & Wang, Yanqian & Zhuang, Guangming & Song, Gongfei, 2022. "Dynamic-memory event-based asynchronous dissipative filtering for T-S fuzzy singular semi-Markov jump systems against multi-cyber attacks," Applied Mathematics and Computation, Elsevier, vol. 431(C).

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