IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v51y2020i1p116-132.html
   My bibliography  Save this article

Sensor fault diagnosis in fractional-order singular systems using unknown input observer

Author

Listed:
  • Fateme Pourdadashi Komachali
  • Masoud Shafiee

Abstract

This paper investigates the design of an unknown input observer for sensor fault diagnosis in linear fractional-order singular systems. The considered system is rectangular in general form. The necessary and sufficient conditions for the existence of the proposed observer are derived, and a systematic design approach is presented. The designed observer is nonsingular and uses only the original coefficient matrices to reconstruct the sensor faults. The proposed diagnosis method can decouple both the unknown inputs appearing in the system dynamics and the output equation, using only the available inputs and measurable output signals. The asymptotic stability conditions of the designed observer are obtained in terms of linear matrix inequalities. Moreover, the proposed approach is developed for sensor fault diagnosis in fractional-order singular one-sided Lipschitz systems. The convergence conditions of the designed nonlinear observer are derived in terms of linear matrix inequalities by introducing a continuous frequency distributed equivalent model and using indirect Lyapunov approach. Finally, the proposed approach is applied to a machine infinite bus system and a numerical example to demonstrate its effectiveness.

Suggested Citation

  • Fateme Pourdadashi Komachali & Masoud Shafiee, 2020. "Sensor fault diagnosis in fractional-order singular systems using unknown input observer," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(1), pages 116-132, January.
  • Handle: RePEc:taf:tsysxx:v:51:y:2020:i:1:p:116-132
    DOI: 10.1080/00207721.2019.1701135
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2019.1701135
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207721.2019.1701135?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:51:y:2020:i:1:p:116-132. 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.