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Distributed Resilient Fusion Filtering for Nonlinear Systems with Random Sensor Delays: Optimized Algorithm Design and Boundedness Analysis

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Abstract

This paper is concerned with the distributed resilient fusion filtering (DRFF) problem for a class of time-varying multi-sensor nonlinear stochastic systems (MNSSs) with random sensor delays (RSDs). The phenomenon of the RSDs is modeled by a set of random variables with certain statistical features. In addition, the nonlinear function is handled via Taylor expansion in order to deal with the nonlinear fusion filtering problem. The aim of the addressed issue is to propose a DRFF scheme for MNSSs such that, for both RSDs and estimator gain perturbations, certain upper bounds of estimation error covariance (EEC) are given and locally minimized at every sample time. In the light of the obtained local filters, a new DRFF algorithm is developed via the matrix-weighted fusion method. Furthermore, a sufficient condition is presented, which can guarantee that the local upper bound of the EEC is bounded. Finally, a numerical example is provided, which can show the usefulness of the developed DRFF approach.

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Author information

Authors and Affiliations

  1. School of Automation, Harbin University of Science and Technology, Harbin, 150080, China

    Jun Hu

  2. Department of Mathematics, Harbin University of Science and Technology, Harbin, 150080, China

    Jun Hu & Zhibin Hu

  3. Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems, Harbin University of Science and Technology, Harbin, 150080, China

    Hongli Dong

  4. Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing, 163318, China

    Hongjian Liu

  5. School of Mathematics-Physics and Finance, Anhui Polytechnic University, Wuhu, 241000, China

    Jun Hu

Authors
  1. Jun Hu
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  2. Zhibin Hu
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  3. Hongli Dong
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  4. Hongjian Liu
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Corresponding author

Correspondence to Jun Hu.

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The authors declare no conflict of interest.

Additional information

This work was supported in part by the National Natural Science Foundation of China under Grant Nos. 12171124, 61873058, and 61673141, the Natural Science Foundation of Heilongjiang Province of China under Grant No. ZD2022F003, the Key Foundation of Educational Science Planning in Heilongjiang Province of China under Grant No. GJB1422069, and the Alexander von Humboldt Foundation of Germany.

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Hu, J., Hu, Z., Dong, H. et al. Distributed Resilient Fusion Filtering for Nonlinear Systems with Random Sensor Delays: Optimized Algorithm Design and Boundedness Analysis. J Syst Sci Complex 36, 1423–1442 (2023). https://doi.org/10.1007/s11424-023-2183-z

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  • DOI: https://doi.org/10.1007/s11424-023-2183-z

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