IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v53y2022i6p1288-1297.html
   My bibliography  Save this article

Probabilistic-constrained distributed fusion filtering for a class of time-varying systems over sensor networks: a torus-event-triggering mechanism

Author

Listed:
  • Fanrong Qu
  • Xia Zhao
  • Xinmeng Wang
  • Engang Tian

Abstract

This paper investigates the problem of distributed fusion over sensor networks with probabilistic constraints and stochastic perturbations. In order to save the bandwidth resources, a new event-triggering mechanism (ETM), called torus-event-triggering mechanism (TETM), is utilised for data transmission. Compared with the traditional ETMs, the TETM has two thresholds, which will not only discard the sampling data smaller than the lower threshold but also hold back the packet larger than the upper threshold. The main purpose of this paper is to design a time-varying distributed fusion filter such that: (1) the probability of the filtering error falling in a given ellipsoid domain is greater than a specified value and (2) the ellipsoidal set is minimised in the sense of matrix norm at each time point. To achieve the above-mentioned purpose, sufficient conditions are given to obtain the global fusion with the help of the recursive linear matrix inequality technique. The desired local filter parameters are then computed by solving an optimisation problem with some inequality constraints. Finally, a numerical simulation is given to illustrate the effectiveness and applicability of the proposed distributed fusion strategy.

Suggested Citation

  • Fanrong Qu & Xia Zhao & Xinmeng Wang & Engang Tian, 2022. "Probabilistic-constrained distributed fusion filtering for a class of time-varying systems over sensor networks: a torus-event-triggering mechanism," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(6), pages 1288-1297, April.
    • Handle: RePEc:taf:tsysxx:v:53:y:2022:i:6:p:1288-1297
    DOI: 10.1080/00207721.2021.1998721
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2021.1998721
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2021.1998721?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Dan & Wang, Zidong & Liu, Yurong & Xue, Changfeng & Alsaadi, Fuad E., 2023. "Distributed Recursive Filtering for Time-Varying Systems with Dynamic Bias over Sensor Networks: Tackling Packet Disorders," Applied Mathematics and Computation, Elsevier, vol. 440(C).
    2. Guo, Xinchen & Wei, Guoliang, 2023. "Distributed sliding mode consensus control for multiple discrete-Time Euler-Lagrange systems," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    3. Manman Luo & Baibin Yang & Zhaolei Yan & Yuwen Shen & Manfeng Hu, 2024. "The Dynamic Event-Based Non-Fragile H ∞ State Estimation for Discrete Nonlinear Systems with Dynamical Bias and Fading Measurement," Mathematics, MDPI, vol. 12(18), pages 1-16, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tsysxx:v:53:y:2022:i:6:p:1288-1297. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.