IDEAS home Printed from https://ideas.repec.org/a/hin/jnddns/9923496.html
   My bibliography  Save this article

A Distributed Model Predictive Control for Multiple Mobile Robots with the Model Uncertainty

Author

Listed:
  • Wei Shang
  • Hanzong Zhu
  • Yurong Pan
  • Xiuhong Li
  • Daode Zhang
  • Ya Jia

Abstract

In this paper, a distributed predictive control with the model uncertainty which uses the data-driven strategy and robust theory (data-driven RDMPC) is proposed for the formation control of multiple mobile robots. The robust performance objective minimization is applied to replace the quadratic performance objective minimization to establish the optimization problem, where the model uncertainty is considered in the distributed system. The control policy is derived by applying the data-driven strategy, and the future predictive value is obtained by employing the linear law in the historical data. Lyapunov theory is referred to analyze the stability of the mobile robot formation system. The effectiveness of the proposed method is proved by a set of simulation experiments.

Suggested Citation

  • Wei Shang & Hanzong Zhu & Yurong Pan & Xiuhong Li & Daode Zhang & Ya Jia, 2021. "A Distributed Model Predictive Control for Multiple Mobile Robots with the Model Uncertainty," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-22, June.
    • Handle: RePEc:hin:jnddns:9923496
    DOI: 10.1155/2021/9923496
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/ddns/2021/9923496.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/ddns/2021/9923496.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/9923496?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
    ---><---

    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:hin:jnddns:9923496. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.