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浙江大学学报(工学版)
Journal of ZheJiang University (Engineering Science)  2022, Vol. 56 Issue (3): 436-443    DOI: 10.3785/j.issn.1008-973X.2022.03.002
    
Improved switching-gain adaptation based sliding mode control for trajectory tracking of underactuated unmanned surface vessels
Rui YU1(),Xue-feng XU1,2,Hua ZHOU1,*(),Hua-yong YANG1
1. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
2. Jiujiang Branch of Tianjin Navigation Instrument Research Institute, Jiujiang 332007, China
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Abstract  

An improved switching-gain adaptation (ISGA) based sliding mode control algorithm was proposed for trajectory tracking of underactuated unmanned surface vessels (USVs), aiming to the challenges which the parametric uncertainties and nonlinearity of disturbance bring to the precise trajectory tracking control of underactuated USVs. In the algorithm, the backstepping and PI sliding mode control were combined to ensure an underactuated USV tracking and maintain the desired trajectory. In addition, an ISGA algorithm based on ideal switching gain was adopted to improve the robustness and suppress the chattering phenomenon. The global exponential stability of the trajectory tracking system was verified by the Lyapunov’s direct method. Simulation results show that the algorithm has the advantages of strong robustness, weak chattering and high accuracy. Compared with the two state-of-the-art algorithms, the position-attitude control accuracy of the proposed algorithm is improved by more than 25.0%.

Key words： underactuated unmanned surface vessels      improved switching-gain adaptation(ISGA)      sliding mode control      trajectory tracking      exponential convergence     
Received: 30 April 2021      Published: 29 March 2022
CLC:  TP 24  
Fund:  国家自然科学基金资助项目（51890885）；国家重点研发计划资助项目（2018YFB2001203）；国家自然科学基金创新研究群体项目（51821093）
Corresponding Authors: Hua ZHOU     E-mail: yuruismail@163.com;hzhou@zju.edu.cn
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Rui YU
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Cite this article:

Rui YU,Xue-feng XU,Hua ZHOU,Hua-yong YANG. Improved switching-gain adaptation based sliding mode control for trajectory tracking of underactuated unmanned surface vessels. Journal of ZheJiang University (Engineering Science), 2022, 56(3): 436-443.

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https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2022.03.002     OR     https://www.zjujournals.com/eng/Y2022/V56/I3/436


基于改进切换增益自适应率的欠驱动USV滑模轨迹跟踪控制

针对参数的不确定性和外界干扰的非线性给欠驱动无人艇(USV)的精确轨迹跟踪控制带来的挑战，提出基于改进切换增益自适应率（ISGA）的欠驱动USV滑模轨迹跟踪控制算法. 该算法结合反步法和PI滑模控制，以保证欠驱动USV跟踪并保持期望的轨迹；采用基于理想增益的ISGA算法，以提高系统的鲁棒性和抑制滑模抖振现象. 借助李雅普诺夫直接法证明轨迹跟踪控制系统的全局指数稳定性. 仿真结果显示，所提算法具有鲁棒性强、滑模抖振弱和控制精度高等优点. 相较2种先进的轨迹跟踪控制算法，所提算法的位姿控制精度提高超过25.0%.


关键词： 欠驱动无人艇,  改进切换增益自适应率(ISGA),  滑模控制,  轨迹跟踪,  指数收敛 
Fig.1 Reference frames of underactuated USV
Fig.2 Control principle based on improved switching-gain adaptation
参数 数值 参数 数值
$ {m_{11}}/{\text{kg}} $ 200 ${r_{{\rm{d}}, \max } }/({\text{rad} } \cdot { {\text{s} }^{ - 1} })$ 2
${m_{33} }/({\text{kg} } \cdot { {\text{m} }^{ - 2} })$ 80 $ {d_{22}}/({\text{kg}} \cdot {{\text{s}}^{ - 1}}) $ 100
$ {\hat m_{ii}} $ $0.7{m_{ii} }$ $ {d_{\rm{u}}}/{\text{N}},{d_{\rm{v}}}/{\text{N}} $ $10\text{Rand}\;(·)$
${d_{\rm{r}}}$ $20\text{Rand}\;(·)$ $ {\hat d_{\rm{u}}},{\hat d_{\rm{v}}} $ 0
$ {d_{11}}/({\text{kg}} \cdot {{\text{s}}^{ - 1}}) $ 70 $ {m_{22}}/{\text{kg}} $ 250
$ {d_{33}}/({\text{kg}} \cdot {{\text{m}}^2} \cdot {{\text{s}}^{ - 1}}) $ 50 $ {\hat d_{\rm{r}}} $ 0
$ {\hat d_{ii}} $ $0.7{d_{ii} }$ — —
Tab.1 Simulation parameters of underactuated USV
参数 数值 参数 数值 参数 数值 参数 数值
$ {\lambda _0} $ 0.04 $ {\lambda _6} $ 0.23 $ {\eta _2} $ 0.01 $ {k_5} $ 1.00
$ {\lambda _1} $ 0.08 $ {\lambda _8} $ 10.00 $ {k_1} $ 3.01 $ {k_6} $ 1.00
$ {\lambda _2} $ 0.16 $ {\lambda _9} $ 9.48 $ {k_2} $ 1.00 $ {k_7} $ 2.00
$ {\lambda _3} $ 9.36 $ {\eta _3} $ 0.01 $ {k_3} $ 3.00 $ {k_8} $ 1.00
$ {\lambda _4} $ 10.00 $ {\eta _1} $ 0.01 $ {k_4} $ 1.00 $ {k_9} $ 2.03
Tab.2 Parameters of controller based on improved switching-gain adaptation
Fig.3 Tracking trajectory of underactuated USV
算法 $ {E_{{\text{RMS}}}} $ $ {F_{{\text{RMS}}}} $ ts/s
本研究 0.90 328.67 3.38
文献[18] 1.47 110.54 3.00
文献[20] 1.20 267.81 3.39
Tab.3 Trajectory tracking errors of different algorithms
Fig.4 Tracking errors of underactuated USV
Fig.5 Velocities of improved switching-gain adaptation based underactuated USV
Fig.6 Sliding surfaces of underactuated USV
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