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Adaptive consensus-based distributed H∞ filtering with switching topology subject to partial information on transition probabilities

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  • Zhu, Fengzeng
  • Liu, Xu
  • Peng, Li

Abstract

This article is dedicated to designing distributed state estimators for time-varying delay systems. The filtering network communication topology is time-varying, and it is presumed that the switching mechanism follows a homogeneous Markov chain, with partially unknown information in the probability transition matrix. An adaptive event-triggered mechanism is embedded in the sensor network, which reduces unnecessary communication data and saves communication resources. By utilising the mode-dependent Lyapunov function, sufficient conditions are deduced to ensure the H∞-consensus performance for the filtering error dynamics. Then, some intensive analysis is performed to obtain the explicit expressions of the distributed H∞ state estimator by introducing slack variables and free-connection weighting matrices. Finally, two numerical simulations are proposed to demonstrate the effectiveness of theoretical results.

Suggested Citation

  • Zhu, Fengzeng & Liu, Xu & Peng, Li, 2021. "Adaptive consensus-based distributed H∞ filtering with switching topology subject to partial information on transition probabilities," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    • Handle: RePEc:eee:apmaco:v:411:y:2021:i:c:s0096300321006172
    DOI: 10.1016/j.amc.2021.126534
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    References listed on IDEAS

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    1. Duan, Ruirui & Li, Junmin, 2020. "Finite-time distributed H∞ filtering for Takagi-Sugeno fuzzy system with uncertain probability sensor saturation under switching network topology: Non-PDC approach," Applied Mathematics and Computation, Elsevier, vol. 371(C).
    2. Wu, Yuyan & Cheng, Jun & Zhou, Xia & Cao, Jinde & Luo, Mengzhuo, 2021. "Asynchronous filtering for nonhomogeneous Markov jumping systems with deception attacks," Applied Mathematics and Computation, Elsevier, vol. 394(C).
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    Cited by:

    1. Xueming Qian & Baotong Cui, 2022. "Mobile Sensor Networks for Finite-Time Distributed H ∞ Consensus Filtering of 3D Nonlinear Distributed Parameter Systems with Randomly Occurring Sensor Saturation," Mathematics, MDPI, vol. 10(17), pages 1-24, September.
    2. Shen Lei & Ren Xiangfang & Wu Jianbin & Chen Han & Ouyang Jianyong, 2022. "Study on body area network of smart clothing for physiological monitoring," International Journal of Distributed Sensor Networks, , vol. 18(2), pages 15501477211, February.

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