IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v52y2021i10p2003-2019.html
   My bibliography  Save this article

Output-based decentralised event-triggered dissipative control of NCSs under aperiodic DoS attacks

Author

Listed:
  • Lisai Gao
  • Fuqiang Li
  • Jingqi Fu

Abstract

This paper studies output-based decentralised event-triggered dissipative control of NCSs under aperiodic DoS attacks. Firstly, to save constrained system resources such as network bandwidth, using information on aperiodic DoS attacks, an output-based decentralised resilient event-triggered mechanism (ETM) is introduced. Secondly, a switched system model is built, which characterises effects of aperiodic DoS attacks, decentralised resilient ETM and disturbances in a unified framework. Thirdly, sufficient conditions are derived such that the system is exponentially stable and strictly $ (\mathcal {G} $ (G, $ \mathcal {H} $ H, $ \mathcal {I}) $ I)-dissipative, which establish quantitative relationships among aperiodic DoS attacks, decentralised resilient ETM, disturbances and system performance. Further, co-design conditions are presented to compute parameters of switched dynamic output feedback controller and decentralised resilient ETM simultaneously. Finally, examples illustrate effectiveness of the proposed method.

Suggested Citation

  • Lisai Gao & Fuqiang Li & Jingqi Fu, 2021. "Output-based decentralised event-triggered dissipative control of NCSs under aperiodic DoS attacks," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(10), pages 2003-2019, July.
    • Handle: RePEc:taf:tsysxx:v:52:y:2021:i:10:p:2003-2019
    DOI: 10.1080/00207721.2021.1874075
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2021.1874075
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2021.1874075?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. 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).

    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:52:y:2021:i:10:p:2003-2019. 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.