IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v55y2024i5p858-875.html
   My bibliography  Save this article

Robust model predictive control for perturbed nonlinear systems via an error differential-integral based event-triggered approach

Author

Listed:
  • Ning He
  • Jiawei Du
  • Zhongxian Xu
  • Fuan Cheng

Abstract

This paper aims to establish a new event-triggered model predictive control (MPC) strategy for perturbed nonlinear systems working in a networked environment, which can effectively save the computation and communication resources while ensuring control performance. The core of the framework is a new event-triggered mechanism, which is built by combining the differential and integral (D-I) information of the error between the optimal state and the actual state in a pre-specified time horizon. Based on such a triggering mechanism, a D-I based event-triggered robust MPC algorithm is proposed to stabilise the system and reduce the computation/communication resource consumption. In addition, sufficient conditions to ensure the feasibility and stability of the proposed MPC algorithm and avoid Zeno behaviour are obtained through rigorous theoretical analysis. Finally, the proposed control framework is implemented in the nonlinear cart-damper-spring and autonomous underwater vehicle systems to verify its effectiveness.

Suggested Citation

  • Ning He & Jiawei Du & Zhongxian Xu & Fuan Cheng, 2024. "Robust model predictive control for perturbed nonlinear systems via an error differential-integral based event-triggered approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 55(5), pages 858-875, April.
    • Handle: RePEc:taf:tsysxx:v:55:y:2024:i:5:p:858-875
    DOI: 10.1080/00207721.2023.2300715
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2023.2300715
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2023.2300715?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:55:y:2024:i:5:p:858-875. 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.