Robust adaptive tracking control of UMSVs under input saturation: A single-parameter learning approach

被引:17
|
作者
Lu, Jinshu [1 ]
Yu, Shulan [1 ]
Zhu, Guibing [1 ]
Zhang, Qiang [2 ]
Chen, Chao [1 ]
Zhang, Jianwei [1 ]
机构
[1] Zhejiang Ocean Univ, Sch Shipping & Maritime, Zhoushan 316022, Zhejiang, Peoples R China
[2] Shandong Jiaotong Univ, Nav Coll, Weihai 264209, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
Unmanned marine surface vessel; Trajectory tracking control; Nonparametric uncertainty; Single parameter learning; Input saturation; UNMANNED SURFACE VEHICLE; UNKNOWN DYNAMICS; TRAJECTORY TRACKING; VESSELS; DISTURBANCE; SHIPS; SUBJECT; SYSTEMS;
D O I
10.1016/j.oceaneng.2021.108791
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 investigates the robust adaptive trajectory tracking control problem for unmanned marine surface vessels (UMSVs) subject to nonparametric uncertainties and external disturbances under input saturation. The non-smooth saturation nonlinearity is replaced by the Gaussian error function. The lumped uncertain term including nonparametric uncertainties, external disturbances and approximation error is formulated by the linear parameterization-like form with a single unknown parameter. Combining the parameter adaptive technique with backstepping design tool, single parameter learning-based tracking control schemes are developed, which involves both full state feedback and output feedback control. The theoretical analysis indicates that under our proposed schemes, all signals in the closed-loop trajectory tracking control system are bounded. Simulation results and comparison illustrate the effectiveness of the developed schemes.
引用
收藏
页数:13
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