IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v53y2022i16p3408-3425.html
   My bibliography  Save this article

Performance-improved finite-time fault-tolerant control for linear uncertain systems with intermittent faults: an overshoot suppression strategy

Author

Listed:
  • Miao Cai
  • Xiao He
  • Donghua Zhou

Abstract

This paper presents a novel prespecified finite-time and overshoot-restrained fault-tolerant tracking control scheme to compensate the intermittent faults in linear uncertain systems. Starting from the system tracking error dynamics model, we design a speed excitation function to improve the response speed of the control. A finite-time performance index function is established in the zero-sum game framework for the fault-free $ \mathcal {H}_{\infty } $ H∞ optimal control policy. Based on Lyapunov stability theory, a fault compensation oriented fault estimation and diagnosis method is proposed to ensure the uniformly ultimately bounded stability of tracking errors. It is noteworthy that the proposed speeding fault-tolerant control can accelerate the trajectory tracking, narrow the upper bound of tracking errors and restrain the overshoot. Numerical and practical experiments fully illustrate the effectiveness of the proposed strategy.

Suggested Citation

  • Miao Cai & Xiao He & Donghua Zhou, 2022. "Performance-improved finite-time fault-tolerant control for linear uncertain systems with intermittent faults: an overshoot suppression strategy," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(16), pages 3408-3425, December.
    • Handle: RePEc:taf:tsysxx:v:53:y:2022:i:16:p:3408-3425
    DOI: 10.1080/00207721.2022.2083261
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2022.2083261
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2022.2083261?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. Liyuan Shao & Yong Zhang & Xiujuan Zheng & Xin He & Yufeng Zheng & Zhiwei Liu, 2023. "A Review of Remaining Useful Life Prediction for Energy Storage Components Based on Stochastic Filtering Methods," Energies, MDPI, vol. 16(3), pages 1-22, February.

    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:16:p:3408-3425. 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.