IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v45y2014i7p1518-1527.html
   My bibliography  Save this article

A structured filter for Markovian switching systems

Author

Listed:
  • Abdelfettah Hocine
  • Mohammed Chadli
  • Hamid Reza Karimi

Abstract

In this work, a new methodology for the structuring of multiple model estimation schemas is developed. The proposed filter is applied to the estimation and detection of active mode in dynamic systems. The discrete-time Markovian switching systems represented by several linear models, associated with a particular operating mode, are studied. Therefore, the main idea of this work is the subdivision of the models set to some subsets in order to improve the detection and estimation performances. Each subset is associated with sub-estimators based on models of the subset. In order to compute the global estimate and subset probabilities, a global estimator is proposed. Theoretical developments based on a hierarchical decision, leading to more efficiency in detection and state estimation, are proposed. Naturally, these results can be used for fault detection and isolation, using the activation probabilities of operating modes. These results are applied to detect switches in the centre of gravity for vehicle roll dynamics.

Suggested Citation

  • Abdelfettah Hocine & Mohammed Chadli & Hamid Reza Karimi, 2014. "A structured filter for Markovian switching systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(7), pages 1518-1527, July.
    • Handle: RePEc:taf:tsysxx:v:45:y:2014:i:7:p:1518-1527
    DOI: 10.1080/00207721.2014.909094
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2014.909094
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2014.909094?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. Zhou, Yaoyao & Chen, Gang, 2021. "Non-fragile H∞ finite-time sliding mode control for stochastic Markovian jump systems with time delay," Applied Mathematics and Computation, Elsevier, vol. 409(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:45:y:2014:i:7:p:1518-1527. 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.