IDEAS home Printed from https://ideas.repec.org/a/taf/tcybxx/v8y2022i3p233-260.html
   My bibliography  Save this article

Identification of Chua’s chaotic circuit parameters using penguins search optimisation algorithm

Author

Listed:
  • Fouzia Maamri
  • Sofiane Bououden
  • Ilyes Boulkaibet

Abstract

In this paper, the Penguins Search optimisation (PeSOA) Algorithm is used to identify optimal control parameters of the Chua circuit. The PeSOA algorithm, which is one of the nature-inspired algorithms, is mainly based on the collaborative hunting concept of penguins. In this algorithm, each penguin individually starts its search process, then communicates its position and the number of fish found to his group. The main objective of this strategy is to synchronise dives among the group in order to achieve a global solution. In this paper, a PeSOA algorithm is adopted to explore the search space for locating the optimum intervals and identify the unknown Chua’s system parameters without any partial knowledge of the internal structure. The identified parameters, obtained by minimising the objective function between the estimated and the output values of the system, are used to obtain stable oscillations. The obtained results show that the PeSOA algorithm gives accurate results and the identified parameters produce a stable oscillation of Chua’s chaotic circuit.

Suggested Citation

  • Fouzia Maamri & Sofiane Bououden & Ilyes Boulkaibet, 2022. "Identification of Chua’s chaotic circuit parameters using penguins search optimisation algorithm," Cyber-Physical Systems, Taylor & Francis Journals, vol. 8(3), pages 233-260, July.
    • Handle: RePEc:taf:tcybxx:v:8:y:2022:i:3:p:233-260
    DOI: 10.1080/23335777.2021.1921038
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23335777.2021.1921038
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/23335777.2021.1921038?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:tcybxx:v:8:y:2022:i:3:p:233-260. 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/tcyb .

    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.