IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v52y2021i11p2217-2227.html
   My bibliography  Save this article

Fault diagnosis and fault-tolerant control for T-S fuzzy time-varying delay stochastic distribution systems with actuator and sensor faults

Author

Listed:
  • Yunfeng Kang
  • Lina Yao

Abstract

The problem of fault diagnosis (FD) and fault-tolerant control (FTC) for a class of nonlinear time-varying delay stochastic distribution control (SDC) systems with actuator and sensor faults is investigated in this paper. The Takagi–Sugeno (T-S) model is used to approximate the nonlinear dynamics. The B-spline function is used to approximate the output probability density function (PDF) of the system. According to the output equivalence principle and Laplace transformation, an augmented state vector is designed to solve the time-varying delay problem. An augmented state adaptive diagnosis observer is proposed to estimate the system state, actuator and sensor faults simultaneously. A new fault-tolerant control algorithm is designed based on the PI control strategy to compensate sensor fault and actuator faults simultaneously. The sensor fault is compensated through the information obtained by the observer. The PI controller can compensate for the influence of the actuator fault, and the output PDF of system can still track the desired PDF when fault occurs. Simulation results are provided to show the effectiveness of the proposed method.

Suggested Citation

  • Yunfeng Kang & Lina Yao, 2021. "Fault diagnosis and fault-tolerant control for T-S fuzzy time-varying delay stochastic distribution systems with actuator and sensor faults," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(11), pages 2217-2227, August.
  • Handle: RePEc:taf:tsysxx:v:52:y:2021:i:11:p:2217-2227
    DOI: 10.1080/00207721.2021.1880666
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2021.1880666
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207721.2021.1880666?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.

    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:11:p:2217-2227. 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.