Full Text:   <740>

Summary:  <311>

Suppl. Mater.: 

CLC number: 

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2023-09-20

Cited: 0

Clicked: 965

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Ning WANG

https://orcid.org/0000-0003-1745-1425

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE A 2023 Vol.24 No.9 P.749-761

http://doi.org/10.1631/jzus.A2300184


Finite-time path following control of a sailboat with actuator failure and unknown sideslip angle


Author(s):  Yujin WU, Kangjian SHAO, Ning WANG, Zhongchao DENG

Affiliation(s):  Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China; more

Corresponding email(s):   n.wang@ieee.org

Key Words:  Sailboat, Sideslip angle, Sideslip angle observer, Finite-time control (FC), Path following


Share this article to: More |Next Article >>>

Yujin WU, Kangjian SHAO, Ning WANG, Zhongchao DENG. Finite-time path following control of a sailboat with actuator failure and unknown sideslip angle[J]. Journal of Zhejiang University Science A, 2023, 24(9): 749-761.

@article{title="Finite-time path following control of a sailboat with actuator failure and unknown sideslip angle",
author="Yujin WU, Kangjian SHAO, Ning WANG, Zhongchao DENG",
journal="Journal of Zhejiang University Science A",
volume="24",
number="9",
pages="749-761",
year="2023",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A2300184"
}

%0 Journal Article
%T Finite-time path following control of a sailboat with actuator failure and unknown sideslip angle
%A Yujin WU
%A Kangjian SHAO
%A Ning WANG
%A Zhongchao DENG
%J Journal of Zhejiang University SCIENCE A
%V 24
%N 9
%P 749-761
%@ 1673-565X
%D 2023
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2300184

TY - JOUR
T1 - Finite-time path following control of a sailboat with actuator failure and unknown sideslip angle
A1 - Yujin WU
A1 - Kangjian SHAO
A1 - Ning WANG
A1 - Zhongchao DENG
J0 - Journal of Zhejiang University Science A
VL - 24
IS - 9
SP - 749
EP - 761
%@ 1673-565X
Y1 - 2023
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2300184


Abstract: 
Suffering from actuator failure and complex sideslip angle, the motion control of a sailboat becomes challenging. In this paper, an improved double finite-time observer-based line-of-sight guidance and finite-time control (IDFLOS-FC) scheme is presented for path following of sailboats. The salient features of the proposed IDFLOS-FC scheme are as follows: (1) Considering the problem of actuator failure, an actuator failure model is introduced into the dynamics model of a sailboat. (2) The time-varying sideslip angle of the sailboat is accurately observed by the double finite-time sideslip observers (DFSOs), which reduces the error in line-of-sight (LOS) guidance. (3) A radial basis function (RBF) neural network is used to fit the uncertainty of the model, and the upper bound of the sum of fault effects and external disturbances is estimated based on adaptive theory, so that the controller has accurate tracking and interference suppression. (4) According to the Lyapunov method, the system is finite-time stable. Finally, simulation was used to validate the effectiveness of the method.

具有执行器故障和未知侧滑角的帆船有限时间路径跟踪控制

作者:吴玉金1,邵康建1,王宁2,邓忠超1
机构:1哈尔滨工程大学,水下机器人重点实验室,中国哈尔滨,150001;2大连海事大学,海洋工程学院,中国大连,116026
目的:在实际航行中,无人帆船存在执行器故障问题以及未知漂角,使得帆船的路径跟踪变得极具挑战性。本文考虑了无人帆船的执行器故障,并设计了一种有限时间漂角观测器来观测未知漂角,以提高无人帆船的路径跟踪精度。
创新点:1.设计双有限时间漂角观测器,能够观测时变的漂角,适用于更复杂的工况;2.设计一种参数自适应调整的非奇异终端滑模,用以增强系统的鲁棒性;3.采用RBF神经网络最小参数估计法对无人帆船模型的不确定性部分进行估计,设计一种基于自适应参数调整滑模的容错控制方法,并证明航向控制系统的误差具有有限时间收敛性。
方法:1.设计双有限时间漂角观测器,用于观测未知漂角;2.考虑执行器故障,利用反步法与滑模控制法,推导出合适的控制律;3.通过仿真模拟,中途增加故障的方式来证实所设计方案的鲁棒性和可靠性。
结论:1.所设计的双有限时间漂角观测器能够精确观测对未知漂角;2.所提出的IDFLOS-FC方案能在执行器失效、漂角随时间变化和未知外部扰动的条件下实现无人驾驶帆船的精确路径跟踪,并能在添加故障时精确跟踪所需的路径,这充分证明了IDFLOS-FC方案的可靠性和优越性。

关键词:漂角观测器;视线制导;有限时间控制;帆船;路径跟踪

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]ChenM, JiangB, CuiRX, 2016. Actuator fault-tolerant control of ocean surface vessels with input saturation. International Journal of Robust and Nonlinear Control, 26(3):542-564.

[2]CuiRX, ZhangX, CuiD, 2016. Adaptive sliding-mode attitude control for autonomous underwater vehicles with input nonlinearities. Ocean Engineering, 123:45-54.

[3]DengYJ, ZhangXK, ZhangGQ, 2020. Line-of-sight-based guidance and adaptive neural path-following control for sailboats. IEEE Journal of Oceanic Engineering, 45(4):1177-1189.

[4]Dos SantosDH, GoncalvesLMG, 2019. A gain-scheduling control strategy and short-term path optimization with genetic algorithm for autonomous navigation of a sailboat robot. International Journal of Advanced Robotic Systems, 16(1):172988141882183.

[5]EmamiSA, BanazadehA, 2020. Fault-tolerant predictive trajectory tracking of an air vehicle based on acceleration control. IET Control Theory & Applications, 14(5):750-762.

[6]FossenTI, 2011. Handbook of Marine Craft Hydrodynamics and Motion Control. John Wiley & Sons Ltd., Chichester, UK.

[7]FuMY, LiMY, XieWB, 2018. Finite-time trajectory tracking fault-tolerant control for surface vessel based on time-varying sliding mode. IEEE Access, 6:2425-2433.

[8]GuoB, ChenY, ZhouAJ, 2021. Event trigger-based adaptive sliding mode fault-tolerant control for dynamic systems. Science China Information Sciences, 64(6):169205.

[9]HongSM, HaKN, KimJY, 2020. Dynamics modeling and motion simulation of USV/UUV with linked underwater cable. Journal of Marine Science and Engineering, 8(5):318.

[10]LiY, LiXW, WeiXW, 2023. Sim-real joint experimental verification for an unmanned surface vehicle formation strategy based on multi-agent deterministic policy gradient and line of sight guidance. Ocean Engineering, 270:113661.

[11]LiuT, DongZP, DuHW, 2017. Path following control of the underactuated USV based on the improved line-of-sight guidance algorithm. Polish Maritime Research, 24(1):3-11.

[12]LiuZQ, 2022. Improved ELOS based path following control for underactuated surface vessels with roll constraint. Ocean Engineering, 245:110348.

[13]LiuZX, ZhangYM, YuX, et al., 2016. Unmanned surface vehicles: an overview of developments and challenges. Annual Reviews in Control, 41:71-93.

[14]MaY, NieZQ, HuSL, et al., 2021. Fault detection filter and controller co-design for unmanned surface vehicles under DoS attacks. IEEE Transactions on Intelligent Transportation Systems, 22(3):1422-1434.

[15]ManleyJE, 2008. Unmanned surface vehicles, 15 years of development. OCEANS 2008, p.1-4.

[16]PettersenKY, LefeberE, 2001. Way-point tracking control of ships. Proceedings of the 40th IEEE Conference on Decision and Control, p.940-945.

[17]QinHD, LiCP, SunYC, 2020. Adaptive neural network-based fault-tolerant trajectory-tracking control of unmanned surface vessels with input saturation and error constraints. IET Intelligent Transport Systems, 14(5):356-363.

[18]ShaoKJ, WuYJ, WangN, et al., 2023. Sailboat path following control based on LOS with sideslip angle observation and finite-time backstepping. S-Cube 2022: Sensor Systems and Software, p.63-78.

[19]VielC, VautierU, WanJ, et al., 2018. Position keeping control of an autonomous sailboat. IFAC-PapersOnLine, 51(29):14-19.

[20]WanL, CaoY, SunYC, et al., 2022. Fault-tolerant trajectory tracking control for unmanned surface vehicle with actuator faults based on a fast fixed-time system. ISA Transactions, 130:79-91.

[21]WangN, DengZC, 2020. Finite-time fault estimator based fault-tolerance control for a surface vehicle with input saturations. IEEE Transactions on Industrial Informatics, 16(2):1172-1181.

[22]WangN, AhnCK, 2021. Coordinated trajectory-tracking control of a marine aerial-surface heterogeneous system. IEEE/ASME Transactions on Mechatronics, 26(6):3198-3210.

[23]WangN, SuSF, 2021. Finite-time unknown observer-based interactive trajectory tracking control of asymmetric underactuated surface vehicles. IEEE Transactions on Control Systems Technology, 29(2):794-803.

[24]WangN, SunZ, YinJC, et al., 2018. Finite-time observer based guidance and control of underactuated surface vehicles with unknown sideslip angles and disturbances. IEEE Access, 6:14059-14070.

[25]WangN, GaoY, ZhaoH, et al., 2021. Reinforcement learning-based optimal tracking control of an unknown unmanned surface vehicle. IEEE Transactions on Neural Networks and Learning Systems, 32(7):3034-3045.

[26]WangN, ZhangYH, AhnCK, et al., 2022. Autonomous pilot of unmanned surface vehicles: bridging path planning and tracking. IEEE Transactions on Vehicular Technology, 71(3):2358-2374.

[27]WangXM, SongXM, DuLH, 2019. Review and application of unmanned surface vehicle in China. The 5th International Conference on Transportation Information and Safety, p.1476-1481.

[28]WilleKL, HassaniV, SprengerF, 2016. Modeling and course control of sailboats. IFAC-PapersOnLine, 49(23):532-539.

[29]XiaGQ, WangXW, ZhaoB, et al., 2019. LOS guidance law for path following of USV based on sideslip observer. Chinese Automation Congress, p.1312-1316.

[30]XiaoL, JouffroyJ, 2014. Modeling and nonlinear heading control of sailing yachts. IEEE Journal of Oceanic Engineering, 39(2):256-268.

[31]XuMCX, WangYT, HanZQ, et al., 2020. Unmanned surface vehicle path following based on path parameter description. Global Oceans: Singapore–U.S. Gulf Coast, p.1-6.

[32]ZhouZT, ZhongMY, WangYQ, 2019. Fault diagnosis observer and fault-tolerant control design for unmanned surface vehicles in network environments. IEEE Access, 7:173694-173702.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE