Robust Finite-Time Control of a Multi-AUV Formation Based on Prescribed Performance

被引:5
|
作者
Li, Juan [1 ,2 ]
Tian, Zhenyang [2 ]
Zhang, Honghan [2 ]
Li, Wenbo [2 ]
机构
[1] Harbin Engn Univ, Key Lab Underwater Robot Technol, Harbin 150001, Peoples R China
[2] Harbin Engn Univ, Coll Intelligent Syst Sci & Engn, Harbin 150001, Peoples R China
基金
中国国家自然科学基金;
关键词
prescribed performance; finite time; robustness; feedback linearization; formation control; UNDERWATER VEHICLES; FEEDBACK SYSTEMS; ADAPTIVE-CONTROL; CONTROL DESIGN; TRACKING; AFFINE;
D O I
10.3390/jmse11050897
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
This paper focuses on the finite-time formation-control problem of a multi-AUV formation under unknown perturbations with prescribed performance. First, the nonlinear AUV model is transformed into a second-order integral model using feedback linearization. Suitable prescribed performance functions are selected to constrain the control errors of AUVs within a preset range and convert AUV tracking errors into unconstrained tracking errors using an error-conversion function to facilitate controller design. Finite-time sliding-mode disturbance observers are designed for unknown disturbances in the ocean so that they can accurately estimate the unknown disturbances in finite time. Based on the unconstrained tracking error and the unknown disturbance observer, the fast terminal sliding-mode formation controller is designed so that the multi-AUV formation can converge in finite time. Finally, the simulation experimental results show that the finite-time formation-control method with prescribed performance proposed in this paper can better cancel the unknown disturbance in the ocean in finite time and improve the robustness of the multi-AUV formation control.
引用
收藏
页数:26
相关论文
共 50 条
  • [41] Composite adaptive finite-time control for quadrotors via prescribed performance
    Jiang T.
    Huang J.
    Li B.
    Li, Bin (3120150050@bit.edu.cn), 1600, Elsevier Ltd (357): : 5878 - 5901
  • [42] Finite-time Prescribed Performance Control with RBFNN for the HFV Longitudinal Model
    Zhang, Yuan
    Huang, Wanwei
    Lu, Kunfeng
    Zhong, Honghao
    2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 2821 - 2827
  • [43] A Novel Obstacle Avoidance Consensus Control for Multi-AUV Formation System
    Wang, Linling
    Zhu, Daqi
    Pang, Wen
    Luo, Chaomin
    IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2023, 10 (05) : 1304 - 1318
  • [44] Optimized backstepping-based finite-time containment control for nonlinear multi-agent systems with prescribed performance
    Tang, Li
    Zhang, Liang
    Xu, Ning
    OPTIMAL CONTROL APPLICATIONS & METHODS, 2024, 45 (05): : 2364 - 2382
  • [45] Finite-time dynamic surface control for multi-agent systems with prescribed performance and unknown control directions
    Shan, Huadi
    Xue, Hong
    Hu, Shenglin
    Liang, Hongjing
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2022, 53 (02) : 325 - 336
  • [46] Coordinated control for Multi-AUV systems based on hybrid automata
    Xiang, Xianbo
    Xu, Guohua
    Zhang, Qin
    Xiao, Zhihu
    Huang, Xinhan
    2007 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS, VOLS 1-5, 2007, : 2121 - +
  • [47] The multi-AUV time-varying formation reconfiguration control based on rigid-graph theory and affine transformation?
    Pang, Wen
    Zhu, Daqi
    Liu, Chenxia
    Wang, Linling
    OCEAN ENGINEERING, 2023, 270
  • [48] Robust Finite-Time Attitude Tracking Control of a CMG-Based AUV With Unknown Disturbances and Input Saturation
    Xu, Ruikun
    Tang, Guoyuan
    Han, Lijun
    Huang, Hui
    Xie, De
    IEEE ACCESS, 2019, 7 : 56409 - 56422
  • [49] Fuzzy Observer-Based Finite-Time Prescribed Performance Control of Linear Stepping Motor
    Sun, Yue
    Gao, Chuang
    Zhou, Xin
    IAENG International Journal of Computer Science, 2021, 48 (01)
  • [50] Multi-AUV Formation Predictive Control Based on CNN-LSTM under Communication Constraints
    Li, Juan
    Tian, Zhenyang
    Zhang, Gengshi
    Li, Wenbo
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2023, 11 (04)