IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i8p1350-d1638946.html
   My bibliography  Save this article

Data-Driven Robust Attitude Tracking Control of Unmanned Underwater Vehicles with Performance Constraints

Author

Listed:
  • He-Ning Zhang

    (Hubei Key Laboratory of Modern Manufacturing Quality Engineering, School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China)

  • Run-Ze Chen

    (School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Zi-Yi Liu

    (Hubei Key Laboratory of Modern Manufacturing Quality Engineering, School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China)

  • Zhi-Fu Zhang

    (Hubei Key Laboratory of Modern Manufacturing Quality Engineering, School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China
    School of Mechanical and Electrical Engineering, Hainan University, Haikou 570228, China)

  • Yi-Zhe Huang

    (Hubei Key Laboratory of Modern Manufacturing Quality Engineering, School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China)

Abstract

This paper studies the data-driven attitude tracking control issue for an unmanned underwater vehicle (UUV) with disturbances. First, a new polynomial finite-time prescribed performance function (FTPF) is introduced to avoid the problem of the computation number increasing as the exponential term increases in the conventional exponential FTPF. By using the new polynomial FTPF, the tracking error is converted into a constrained form. Then, an estimator is designed for estimating the unknown pseudo-partitioned Jacobian matrix (PJM) in the linearization model, and a discrete-time nonlinear disturbance observer (DNDO) is adopted for observing unknown disturbances. It is worth noting that the DNDO can avoid the large overshoot by introducing a saturated function. With the help of the estimator for the PJM, the DNDO, and the constrained error, a data-driven robust control strategy with performance constraints is designed to fulfill accurate attitude tracking control of the UUV, which ensures that the tracking error draws into a prescribed region in a predetermined time. Eventually, the control strategy is verified by numerical simulations.

Suggested Citation

  • He-Ning Zhang & Run-Ze Chen & Zi-Yi Liu & Zhi-Fu Zhang & Yi-Zhe Huang, 2025. "Data-Driven Robust Attitude Tracking Control of Unmanned Underwater Vehicles with Performance Constraints," Mathematics, MDPI, vol. 13(8), pages 1-20, April.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:8:p:1350-:d:1638946
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/8/1350/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/13/8/1350/
    Download Restriction: no
    ---><---

    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:13:y:2025:i:8:p:1350-:d:1638946. 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: 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.