IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v56y2025i14p3481-3497.html
   My bibliography  Save this article

An adaptive self-adjusting fuzzy logic-based robust controller formulation for a class of uncertain MIMO nonlinear systems

Author

Listed:
  • Bayram Melih Yilmaz
  • Enver Tatlicioglu
  • Erkan Zergeroglu

Abstract

This study presents a novel continuous controller, in conjunction with a fuzzy logic-based estimator, designed to address the compensation of parametric uncertainty in a category of high-order, multiple-input-multiple-output nonlinear systems. The proposed controller–estimator methodology tackles parametric uncertainties with self-adjusting adaptive fuzzy logic-based robust integral of sign of error algorithm. In the employed adaptive fuzzy logic (AFL) framework, the means and variances of the membership functions are updated online in each iteration, enabling a more accurate estimation of uncertainties. The boundedness of the closed-loop system and asymptotic stability of the error signals are verified via Lyapunov-based arguments. Numerical simulations are additionally presented to evaluate the efficacy of the proposed methodology.

Suggested Citation

  • Bayram Melih Yilmaz & Enver Tatlicioglu & Erkan Zergeroglu, 2025. "An adaptive self-adjusting fuzzy logic-based robust controller formulation for a class of uncertain MIMO nonlinear systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 56(14), pages 3481-3497, October.
    • Handle: RePEc:taf:tsysxx:v:56:y:2025:i:14:p:3481-3497
    DOI: 10.1080/00207721.2025.2470404
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2025.2470404
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2025.2470404?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

    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:56:y:2025:i:14:p:3481-3497. 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.