Adaptive fault-tolerant trajectory tracking control of twin-propeller non-rudder unmanned surface vehicles
This paper studies the fault-tolerant trajectory tracking control problem of twin-propeller non-rudder unmanned surface vehicles (TPNR USVs) subject to propeller faults. Firstly, a propeller model of TPNR USVs is constructed by decomposing propeller thrusts on the body-fixed reference frame. A prope...
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| Published in | Ocean engineering Vol. 285; p. 115294 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.10.2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0029-8018 1873-5258 |
| DOI | 10.1016/j.oceaneng.2023.115294 |
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| Abstract | This paper studies the fault-tolerant trajectory tracking control problem of twin-propeller non-rudder unmanned surface vehicles (TPNR USVs) subject to propeller faults. Firstly, a propeller model of TPNR USVs is constructed by decomposing propeller thrusts on the body-fixed reference frame. A propeller fault model is also established by taking into account floating and loss-of-effectiveness faults. Secondly, to ensure tracking errors stay in reasonable ranges, a novel guaranteed transient performance method is proposed. Meanwhile, corresponding error transformation functions are constructed. Thirdly, by utilizing the excellent nonlinearity approximation performance of neural networks (NNs), an adaptive fault-tolerant trajectory tracking control scheme, which can guarantee TPNR USVs track the desired trajectory quickly and accurately even in the event of propeller faults, is proposed. Finally, the fault-tolerant trajectory tracking performance analysis demonstrates the efficiency of the proposed control scheme.
•A coherent mechanism among propulsion forces, steering moment, and propeller-generated thrusts of TPNR USVs is developed.•The fault-tolerant trajectory tracking control problem of TPNR USVs is studied for the first time. Corresponding, a novel adaptive fault-tolerant control scheme is designed.•The design of propeller thrusts is proposed, which is more suitable for practical applications than giving only the design of the surge force and yaw moment. |
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| AbstractList | This paper studies the fault-tolerant trajectory tracking control problem of twin-propeller non-rudder unmanned surface vehicles (TPNR USVs) subject to propeller faults. Firstly, a propeller model of TPNR USVs is constructed by decomposing propeller thrusts on the body-fixed reference frame. A propeller fault model is also established by taking into account floating and loss-of-effectiveness faults. Secondly, to ensure tracking errors stay in reasonable ranges, a novel guaranteed transient performance method is proposed. Meanwhile, corresponding error transformation functions are constructed. Thirdly, by utilizing the excellent nonlinearity approximation performance of neural networks (NNs), an adaptive fault-tolerant trajectory tracking control scheme, which can guarantee TPNR USVs track the desired trajectory quickly and accurately even in the event of propeller faults, is proposed. Finally, the fault-tolerant trajectory tracking performance analysis demonstrates the efficiency of the proposed control scheme.
•A coherent mechanism among propulsion forces, steering moment, and propeller-generated thrusts of TPNR USVs is developed.•The fault-tolerant trajectory tracking control problem of TPNR USVs is studied for the first time. Corresponding, a novel adaptive fault-tolerant control scheme is designed.•The design of propeller thrusts is proposed, which is more suitable for practical applications than giving only the design of the surge force and yaw moment. |
| ArticleNumber | 115294 |
| Author | Liu, Zhao-Qing Wang, Yu-Long Han, Qing-Long |
| Author_xml | – sequence: 1 givenname: Zhao-Qing orcidid: 0000-0001-5954-3155 surname: Liu fullname: Liu, Zhao-Qing email: patrickliu@shu.edu.cn organization: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China – sequence: 2 givenname: Yu-Long orcidid: 0000-0002-6508-0051 surname: Wang fullname: Wang, Yu-Long email: yulongwang@shu.edu.cn organization: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China – sequence: 3 givenname: Qing-Long orcidid: 0000-0002-7207-0716 surname: Han fullname: Han, Qing-Long email: qhan@swin.edu.au organization: School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC 3122, Australia |
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| Cites_doi | 10.1016/j.automatica.2018.01.026 10.1109/TVT.2021.3050044 10.1109/TSMC.2017.2702705 10.1016/j.oceaneng.2021.109587 10.1109/TII.2018.2877046 10.1109/TNN.2003.811712 10.1109/TCST.2013.2281211 10.1109/TCYB.2016.2573837 10.1016/j.automatica.2016.11.024 10.1109/TNNLS.2019.2944690 10.1109/TNNLS.2018.2876685 10.1016/j.automatica.2009.02.021 10.1016/j.oceaneng.2020.108556 10.1016/j.oceaneng.2020.108099 10.1109/TCST.2018.2834518 10.1016/j.automatica.2021.109501 10.1109/TNNLS.2014.2302477 10.1109/TAC.2021.3074899 10.1016/j.oceaneng.2021.109416 10.1109/TFUZZ.2017.2761323 10.1016/j.conengprac.2012.10.005 10.1016/j.automatica.2004.01.021 10.1109/TIV.2017.2657379 10.1109/TII.2020.3004343 10.1109/TMECH.2022.3188834 10.1109/TAC.2000.880994 10.1109/TII.2021.3133927 10.1016/j.automatica.2016.01.064 10.1109/TIE.2015.2504553 10.1109/TII.2019.2930471 |
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| SubjectTerms | Fault-tolerant control Guaranteed transient performance Trajectory tracking Unmanned surface vehicles |
| Title | Adaptive fault-tolerant trajectory tracking control of twin-propeller non-rudder unmanned surface vehicles |
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