IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v52y2021i12p2505-2517.html
   My bibliography  Save this article

Hierarchical fractional-order Hammerstein system identification

Author

Listed:
  • Soumaya Marzougui
  • Asma Atitallah
  • Saida Bedoui
  • Kamel Abderrahim

Abstract

For the fractional-order Hammerstein system with white noise, the difficulty of identification is that the parameters of the linear and the nonlinear blocks and the fractional order are unknown and the intermediate variable and the states are unmeasurable. To overcome this difficulty, we transform the system from an input nonlinear pseudo-state-space system to an input–output representation and we develop an algorithm based on the Recursive Least Squares, the Levenberg–Marquardt and the Auxiliary Model Principle. The convergence of the identified parameters is studied. The performance of the proposed algorithm are tested by two numerical examples.

Suggested Citation

  • Soumaya Marzougui & Asma Atitallah & Saida Bedoui & Kamel Abderrahim, 2021. "Hierarchical fractional-order Hammerstein system identification," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(12), pages 2505-2517, September.
  • Handle: RePEc:taf:tsysxx:v:52:y:2021:i:12:p:2505-2517
    DOI: 10.1080/00207721.2021.1891324
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2021.1891324
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207721.2021.1891324?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:12:p:2505-2517. 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.