Please wait a minute...
浙江大学学报(工学版)  2022, Vol. 56 Issue (3): 436-443    DOI: 10.3785/j.issn.1008-973X.2022.03.002
机械工程、能源工程     
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
于瑞1(),徐雪峰1,2,周华1,*(),杨华勇1
1. 浙江大学 流体动力与机电系统国家重点实验室,浙江 杭州 310027
2. 天津航海仪器研究所九江分部,江西 九江,332007
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
 全文: PDF(1209 KB)   HTML
摘要:

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    
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
收稿日期: 2021-04-30 出版日期: 2022-03-29
CLC:  TP 24  
基金资助: 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)
通讯作者: 周华     E-mail: yuruismail@163.com;hzhou@zju.edu.cn
作者简介: 于瑞(1995—),男,博士生,从事机电系统集成与控制研究. orcid.org/0000-0002-7834-1740. E-mail: yuruismail@163.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
作者相关文章  
于瑞
徐雪峰
周华
杨华勇

引用本文:

于瑞,徐雪峰,周华,杨华勇. 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[J]. 浙江大学学报(工学版), 2022, 56(3): 436-443.

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.

链接本文:

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

图 1  欠驱动无人艇的参考坐标系
图 2  基于改进切换增益自适应率的控制器原理
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}} $ $0.7{d_{ii} }$
表 1  欠驱动无人艇的仿真参数
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
表 2  基于改进切换增益自适应率的控制器参数
图 3  欠驱动无人艇的跟踪轨迹
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
表 3  不同算法的轨迹跟踪误差
图 4  欠驱动无人艇的跟踪误差
图 5  改进切换增益自适应率的欠驱动无人艇速度
图 6  欠驱动无人艇的滑模面变化
1 GUO G, GAO Z, DONG K Prescribed-time formation control of surface vessels with asymmetric constraints on LOS range and bearing angles[J]. Nonlinear Dynamics, 2021, 104 (4): 3701- 3712
doi: 10.1007/s11071-021-06462-8
2 SHAO G M, MA Y, MALEKIAN R, et al A novel cooperative platform design for coupled USV-UAV systems[J]. IEEE Transactions on Industrial Informatics, 2019, 15 (9): 4913- 4922
doi: 10.1109/TII.2019.2912024
3 陈英龙, 赵勇刚, 周华, 等 大型中层拖网网具系统的仿真研究[J]. 浙江大学学报:工学版, 2014, 48 (4): 625- 632
CHEN Ying-long, ZHAO Yong-gang, ZHOU Hua, et al Simulation study of large mid-water trawl system[J]. Journal of Zhejiang University: Engineering Science, 2014, 48 (4): 625- 632
4 GONZALEZ-GARCIA A, CASTA?EDA H Guidance and control based on adaptive sliding mode strategy for a USV subject to uncertainties[J]. IEEE Journal of Oceanic Engineering, 2021, 46 (4): 1144- 1154
doi: 10.1109/JOE.2021.3059210
5 HOSSEIN M, HAMID J, HAMID A, et al Developing a navigation, guidance and obstacle avoidance algorithm for an unmanned surface vehicle (USV) by algorithms fusion[J]. Ocean Engineering, 2018, 159: 56- 65
doi: 10.1016/j.oceaneng.2018.04.018
6 ZHAO Y, QI X, MA Y, et al Path following optimization for an underactuated USV using smoothly-convergent deep reinforcement learning[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 22 (10): 6208- 6220
7 史剑光, 李德骏, 杨灿军, 等 水下自主机器人接驳碰撞过程分析[J]. 浙江大学学报:工学版, 2015, 49 (3): 497- 504
SHI Jian-guang, LI De-jun, YANG Can-jun, et al Impact analysis during docking process of autonomous underwater vehicle[J]. Journal of Zhejiang University: Engineering Science, 2015, 49 (3): 497- 504
8 GUO G, ZHANG P Asymptotic stabilization of USVs with actuator dead-zones and yaw constraints based on fixed-time disturbance observer[J]. IEEE Transactions on Vehicular Technology, 2020, 69 (1): 302- 316
doi: 10.1109/TVT.2019.2955020
9 ZHANG P, GUO G Fixed-time switching control of underactuated surface vessels with dead-zones: global exponential stabilization[J]. Journal of the Franklin Institute, 2020, 357 (16): 11217- 11241
doi: 10.1016/j.jfranklin.2019.05.030
10 LIU W W, LIU Y C, BUCKNALL R A robust localization method for unmanned surface vehicle (USV) navigation using fuzzy adaptive Kalman filtering[J]. IEEE Access, 2019, 7: 46071- 46083
doi: 10.1109/ACCESS.2019.2909151
11 DO K D Global robust adaptive path-tracking control of underactuated ships under stochastic disturbances[J]. Ocean Engineering, 2016, 111: 267- 278
doi: 10.1016/j.oceaneng.2015.10.038
12 张成举, 王聪, 曹伟, 等 欠驱动USV神经网络自适应轨迹跟踪控制[J]. 哈尔滨工业大学学报, 2020, 52 (12): 1- 7
ZHANG Cheng-ju, WANG Cong, CAO Wei, et al Adaptive neural network trajectory tracking control for underactuated unmanned surface vehicle[J]. Journal of Harbin Institute of Technology, 2020, 52 (12): 1- 7
doi: 10.11918/201905049
13 PAN C Z, LAI X Z, YANG S X, et al A bioinspired neural dynamics-based approach to tracking control of autonomous surface vehicles subject to unknown ocean currents[J]. Neural Computing and Applications, 2015, 26: 1929- 1938
doi: 10.1007/s00521-015-1839-6
14 LIU L, WANG D, PENG Z H Path following of marine surface vehicles with dynamical uncertainty and time-varying ocean disturbances[J]. Neurcomputing, 2016, 173: 799
doi: 10.1016/j.neucom.2015.08.033
15 DONG Z P, WAN L, LI Y M, et al Trajectory tracking control of underactuated USV based on modified backstepping approach[J]. International Journal of Naval Architecture and Ocean Engineering, 2015, 7 (5): 817- 832
doi: 10.1515/ijnaoe-2015-0058
16 ZHOU W, WANG Y, AHN C K, et al Adaptive fuzzy backstepping-based formation control of unmanned surface vehicles with unknown model nonlinearity and actuator saturation[J]. IEEE Transactions on Vehicular Technology, 2020, 69 (12): 14749- 14764
doi: 10.1109/TVT.2020.3039220
17 ASHRAFIUON H, MUSKE K R, MCNINCH L C, et al Sliding-mode tracking control of surface vessels[J]. IEEE Transactions on Industrial Electronics, 2008, 55 (11): 4004- 4012
doi: 10.1109/TIE.2008.2005933
18 XU J, WANG M, QIAO L Dynamical sliding mode control for the trajectory tracking of underactuated unmanned underwater vehicles[J]. Ocean Engineering, 2015, 105: 54- 63
doi: 10.1016/j.oceaneng.2015.06.022
19 SUN Z, ZHANG G, QIAO L, et al Robust adaptive trajectory tracking control of underactuated unmanned surface vessel in fields of marine practice[J]. Journal of Marine Science and Technology, 2018, 23: 950- 957
doi: 10.1007/s00773-017-0524-0
20 SUN Z, ZHANG G, YANG J, et al Research on the sliding mode control for underactuated unmanned surface vessels via parameter estimation[J]. Nonlinear Dynamics, 2018, 91: 1163- 1175
doi: 10.1007/s11071-017-3937-8
21 KAO Y, XIE J, WANG C, et al A sliding mode approach to H∞ non-fragile observer-based control design for uncertain Markovian neutral-type stochastic systems [J]. Automatica, 2015, 52: 218- 226
doi: 10.1016/j.automatica.2014.10.095
22 LEI Q, BOWEN Y, DEFENG W, et al Design of three exponentially convergent robust controllers for the trajectory tracking of autonomous underwater vehicles[J]. Ocean Engineering, 2017, 134: 157- 172
doi: 10.1016/j.oceaneng.2017.02.006
23 LU Y S Sliding-mode disturbance observer with switching-gain adaptation and its application to optical disk drives[J]. IEEE Transactions on Industrial Electronics, 2009, 56 (9): 3743- 3750
doi: 10.1109/TIE.2009.2025719
24 QU Y, XIAO B, FU Z, et al Trajectory exponential tracking control of unmanned surface ships with external disturbance and system uncertainties[J]. ISA Transactions, 2018, 78: 47- 55
doi: 10.1016/j.isatra.2017.12.020
25 BAI K Q, GONG X T, CHEN S H, et al Sliding mode nonlinear disturbance observer-based adaptive back-stepping control of a humanoid robotic dual manipulator[J]. Robotica, 2018, 36 (11): 1728- 1742
doi: 10.1017/S026357471800067X
26 ZHAO X H, ZHANG X Y, YE X F, et al Sliding mode controller design for supercavitating vehicles[J]. Ocean Engineering, 2019, 184: 173- 183
doi: 10.1016/j.oceaneng.2019.04.066
27 劳立明. 基于直驱电液技术的有杆抽油系统运动控制与节能控制研究[D]. 杭州: 浙江大学, 2017: 47-90.
LAO Li-ming. Research on motion control and energy-saving control of sucker rod pumping systems using direct-driven electro-hydraulic technology [D]. Hangzhou: Zhejiang University, 2017: 47-90.
28 WANG N, SU S F Finite-time unknown observer-based interactive trajectory tracking control of asymmetric underactuated surface vehicles[J]. IEEE Transactions on Control Systems Technology, 2019, 99 (2): 794- 803
29 SINISTERRA A J, DHANAK M R, ELLENRIEDER K V Stereovision-based target tracking system for USV operations[J]. Ocean Engineering, 2017, 133: 197- 214
doi: 10.1016/j.oceaneng.2017.01.024
30 FOSSEN T I. Marine control systems: guidance, navigation and control of ships rigs and underwater vehicles [M]. Trondheim: Marine Cybernetics, 2002: 35-120.
31 KHALIL H K. Nonlinear systems [M]. Beijing: Publishing House of Electronics Industry, 2012: 123-125.
[1] 张国澎,李子汉,王浩,郑征. 隔离型交?直流固态变压器前后级一体化滑模控制[J]. 浙江大学学报(工学版), 2022, 56(3): 622-630.
[2] 王玉琼,高松,王玉海,徐艺,郭栋,周英超. 高速无人驾驶车辆轨迹跟踪和稳定性控制[J]. 浙江大学学报(工学版), 2021, 55(10): 1922-1929.
[3] 李静,王晨,张家旭. 基于自适应快速终端滑模的车轮滑移率跟踪控制[J]. 浙江大学学报(工学版), 2021, 55(1): 169-176.
[4] 李剑,汤文成. 基于H∞理论的滚珠丝杠进给系统滑模控制[J]. 浙江大学学报(工学版), 2020, 54(8): 1497-1504.
[5] 朱艺锋,吴党建,白冰洋,岳豪. 单相五电平脉冲整流器滑模比例积分谐振控制[J]. 浙江大学学报(工学版), 2020, 54(8): 1578-1586.
[6] 陈朝萌,周晓军,杨辰龙,吕浩亮,魏杰超. 高速电驱动履带车辆紧急制动控制策略[J]. 浙江大学学报(工学版), 2020, 54(3): 442-449.
[7] 吴海东,司振立. 基于线性矩阵不等式的智能车轨迹跟踪控制[J]. 浙江大学学报(工学版), 2020, 54(1): 110-117.
[8] 吴爱国,吴绍华,董娜. 机械臂非奇异快速终端滑模模糊控制[J]. 浙江大学学报(工学版), 2019, 53(5): 862-871.
[9] 王尧尧, 顾临怡, 陈柏, 吴洪涛. 水下机器人-机械手系统非奇异终端滑模控制[J]. 浙江大学学报(工学版), 2018, 52(5): 934-942.
[10] 潘立, 鲍官军, 胥芳, 张立彬. 六自由度装配机器人的动态柔顺性控制[J]. 浙江大学学报(工学版), 2018, 52(1): 125-132.
[11] 檀盼龙, 孙青林, 陈增强. 自抗扰技术在动力翼伞轨迹跟踪控制中的应用[J]. 浙江大学学报(工学版), 2017, 51(5): 992-999.
[12] 陶国良, 周超超, 尚策. 气动位置伺服嵌入式控制器及控制策略[J]. 浙江大学学报(工学版), 2017, 51(4): 792-799.
[13] 李国飞, 滕青芳, 王传鲁, 张雅琴. 应用滑模控制的四开关逆变器PMSM系统FCS-MPC策略[J]. 浙江大学学报(工学版), 2017, 51(3): 620-627.
[14] 郭凡, 魏建华, 张强, 熊义. 基于级联控制器的液压机位移/压力复合控制[J]. 浙江大学学报(工学版), 2017, 51(10): 1937-1947.
[15] 潘宁, 于良耀, 张雷, 宋健, 张永辉. 电液复合制动系统防抱控制的舒适性[J]. 浙江大学学报(工学版), 2017, 51(1): 9-16.