Rotation matrix-based finite-time trajectory tracking control of AUV with output constraints and input quantization

被引:8
作者
Zhang, Ziyang [1 ]
Xu, Yufei [1 ]
Wan, Lei [1 ]
Chen, Guofang [1 ]
Cao, Yu [1 ]
机构
[1] Harbin Engn Univ, Sci & Technol Underwater Vehicle Lab, Harbin 150001, Peoples R China
基金
中国国家自然科学基金;
关键词
Autonomous underwater vehicle; Rotation matrix; Output constraints; Input quantization; Finite-time command-filtered backstepping; control; Disturbance observer; ATTITUDE TRACKING; STABILITY; SYSTEMS;
D O I
10.1016/j.oceaneng.2023.116570
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 study investigated a rotation -matrix -based finite -time trajectory tracking problem for autonomous underwater vehicles (AUVs) in the presence of output constraints, input quantization, and uncertainties. First, a rotation matrix -based attitude representation is introduced, which allow attitude dynamics to be globally and uniquely represented without unwinding. To satisfy the finite -time stability of AUV tracking control and the output constraints imposed by introducing the new attitude error vector, a novel finite -time command -filtered backstepping controller (FTCFBC) is proposed based on the asymmetrical time -varying barrier Lyapunov function (TVBLF). Subsequently, a second -order auxiliary dynamic system (ADS) is proposed to estimate the negative effects that of input quantization errors. Because the quantized control inputs can be switched at an appropriate earlier or later switching timing depending on the output of the ADS, the negative impact of quantization errors on the control accuracy is reduced. Moreover, an adaptive finite -time disturbance observer (AFTDO) is developed to estimate the lumped uncertainties without prior information on the bounds of the uncertainties. Finally, the results of the theoretical analysis verified that the tracking errors can converge within a finite time. Numerical simulations confirmed the effectiveness of the proposed control scheme.
引用
收藏
页数:23
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共 46 条
  • [1] Robust fixed-time tracking control for underactuated AUVs based on fixed-time disturbance observer
    An, Shun
    Wang, Longjin
    He, Yan
    [J]. OCEAN ENGINEERING, 2022, 266
  • [2] Adaptive backstepping quantized control for a class of unknown nonlinear systems
    Aslmostafa, Ehsan
    Ghaemi, Sehraneh
    Badamchizadeh, Mohammad Ali
    Ghiasi, Amir Rikhtehgar
    [J]. ISA TRANSACTIONS, 2022, 125 : 146 - 155
  • [3] Finite-time stability of continuous autonomous systems
    Bhat, SP
    Bernstein, DS
    [J]. SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2000, 38 (03) : 751 - 766
  • [4] Adaptive fixed-time backstepping control for three-dimensional trajectory tracking of underactuated autonomous underwater vehicles
    Chen, Hongxuan
    Tang, Guoyuan
    Wang, Shufeng
    Guo, Wenxuan
    Huang, Hui
    [J]. OCEAN ENGINEERING, 2023, 275
  • [5] Anti-unwinding sliding mode attitude control via two modified Rodrigues parameter sets for spacecraft
    Dong, Rui-Qi
    Wu, Ai-Guo
    Zhang, Ying
    Duan, Guang-Ren
    [J]. AUTOMATICA, 2021, 129
  • [6] Command Filtered Backstepping
    Farrell, Jay A.
    Polycarpou, Marios
    Sharma, Manu
    Dong, Wenjie
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2009, 54 (06) : 1391 - 1395
  • [7] POSITION AND ATTITUDE TRACKING OF AUVS - A QUATERNION FEEDBACK APPROACH
    FJELLSTAD, OE
    FOSSEN, TI
    [J]. IEEE JOURNAL OF OCEANIC ENGINEERING, 1994, 19 (04) : 512 - 518
  • [8] Fixed-time sliding mode formation control of AUVs based on a disturbance observer
    Gao, Zhenyu
    Guo, Ge
    [J]. IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2020, 7 (02) : 539 - 545
  • [9] Finite-time dynamic positioning control design for surface vessels with external disturbances, input saturation and error constraints
    Gong, Chenglong
    Su, Yixin
    Zhu, Quanxin
    Zhang, Danhong
    Hu, Xin
    [J]. OCEAN ENGINEERING, 2023, 276
  • [10] Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints
    He, Wei
    Chen, Yuhao
    Yin, Zhao
    [J]. IEEE TRANSACTIONS ON CYBERNETICS, 2016, 46 (03) : 620 - 629