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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
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    References listed on IDEAS

    as
    1. Hyunchang Kim & Hyeongki Ahn & Yoonuh Chung & Kwanho You, 2023. "Quadrotor Position and Attitude Tracking Using Advanced Second-Order Sliding Mode Control for Disturbance," Mathematics, MDPI, vol. 11(23), pages 1-15, November.
    2. Runze Chen & Zhenling Wang & Weiwei Che, 2022. "Adaptive Sliding Mode Attitude-Tracking Control of Spacecraft with Prescribed Time Performance," Mathematics, MDPI, vol. 10(3), pages 1-18, January.
    3. Limin Wang & Yiteng Shen & Jingxian Yu & Ping Li & Ridong Zhang & Furong Gao, 2018. "Robust iterative learning control for multi-phase batch processes: an average dwell-time method with 2D convergence indexes," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(2), pages 324-343, January.
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