IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v8y2020i5p756-d356007.html
   My bibliography  Save this article

Preview Control for MIMO Discrete-Time System with Parameter Uncertainty

Author

Listed:
  • Li Li

    (School of Information Management and Statistics, Hubei University of Economics, Wuhan 430205, China)

  • Fucheng Liao

    (School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China)

Abstract

We consider the problems of state feedback and static output feedback preview controller (PC) for uncertain discrete-time multiple-input multiple output (MIMO) systems based on the parameter-dependent Lyapunov function and the linear matrix inequality (LMI) technique in this paper. First, for each component of a reference signal, an augmented error system (AES) containing previewed information is constructed via the difference operator and state augmentation technique. Then, for the AES, the state feedback and static output feedback are introduced, and when considering the output feedback, a previewable reference signal is utilized by modifying the output equation. The preview controllers’ parameter matrices can be achieved from the solution of LMI problems. The superiority of the PC is illustrated via two numerical examples.

Suggested Citation

  • Li Li & Fucheng Liao, 2020. "Preview Control for MIMO Discrete-Time System with Parameter Uncertainty," Mathematics, MDPI, vol. 8(5), pages 1-20, May.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:5:p:756-:d:356007
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/8/5/756/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/8/5/756/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jiang Wu & Fucheng Liao & Masayoshi Tomizuka, 2017. "Optimal preview control for a linear continuous-time stochastic control system in finite-time horizon," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(1), pages 129-137, January.
    2. Yanrong Lu & Fucheng Liao & Jiamei Deng & Huiyang Liu, 2017. "Cooperative global optimal preview tracking control of linear multi-agent systems: an internal model approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(12), pages 2451-2462, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:gam:jmathe:v:8:y:2020:i:5:p:756-:d:356007. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.