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Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed
Wang H(王昊); Liu KZ(刘开周); Li S(李硕)
Department海洋机器人卓越创新中心
Source PublicationNeurocomputing
ISSN0925-2312
2018
Volume275Pages:1478-1489
Indexed BySCI ; EI
EI Accession number20174304289795
WOS IDWOS:000418370200139
Contribution Rank1
Funding OrganizationNational Key Research and Development Program of China under Grants 2016YFC0300801, 2016YFC0301600, 2016YFC0300604, 2017YFC0305901, and in part by the National Natural Science Foundation of China under Grants 61233013, 41376110, 41106085, and in part by the National HighTech Research and Development Program of China under Grant 2014AA09A110, and in part by the Public Science and Technology Research Funds Projects of Ocean under Grant 201505017, and in part by the Instrument Developing Project of the Chinese Academy of Sciences under Grant YZ201441, and in part by the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant XDA13030203, and in part by the Youth Innovation Promotion Association CAS under Grant 2011161, and in part by the Laboratory Foundation of Science and Technology on Water Jet Propulsion under Grant 61422230302162223012, and in part by the Doctoral Scientific Research Foundation of Liaoning Province under Grant 201501035, and in part by the State Key Laboratory of Robotics under Grants 2016-Z02
KeywordCooperative Path Following Uncertainties Autonomous Underwater Vehicles Neural Networks
AbstractThis paper investigates the problem of cooperative path following for a fleet of underactuated autonomous underwater vehicles (AUVs) with uncertain nonlinear dynamics. Path following controllers for individual AUVs are developed to ensure that each AUV converges to the desired position. The coordination mission is completed by reaching synchronization on a suitably defined path variable, even in the presence of partial knowledge of the reference speed. The key features of the proposed cooperative path following design scheme can be summarized as follows. First, the command filter design technique based cooperative path following control strategy is derived by introducing compensating error signals to remove the requirement of the higher derivative of reference signal, and a simplified cooperative path following controller is proposed. Second, a smoothly switching function is designed to yield neural network (NN) based energy-efficient controller. Third, by designing the distributed speed estimator, the global knowledge of the reference speed is relaxed. Finally, all the signals in the closed-loop system are guaranteed to be globally uniformly ultimately bounded (GUUB) under the proposed algorithm, and the path following error is proven to converge to a small neighborhood of the origin. Simulation example is provided to validate the performance of the control strategy.
Language英语
WOS HeadingsScience & Technology ; Technology
WOS SubjectComputer Science, Artificial Intelligence
WOS KeywordDYNAMIC SURFACE CONTROL ; UNCERTAIN NONLINEAR-SYSTEMS ; OUTPUT-FEEDBACK CONTROL ; TRACKING CONTROL ; VESSELS ; LEADER ; ENVIRONMENTS ; NETWORKS ; ROBOTS ; FORM
WOS Research AreaComputer Science
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/21219
Collection海洋机器人卓越创新中心
Corresponding AuthorLi S(李硕)
AffiliationState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
Recommended Citation
GB/T 7714
Wang H,Liu KZ,Li S. Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed[J]. Neurocomputing,2018,275:1478-1489.
APA Wang H,Liu KZ,&Li S.(2018).Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed.Neurocomputing,275,1478-1489.
MLA Wang H,et al."Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed".Neurocomputing 275(2018):1478-1489.
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