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Adaptive neural control for cooperative path following of marine surface vehicles: state and output feedback
Wang H(王昊); Wang D(王丹); Peng ZH(彭周华)
作者部门水下机器人研究室
关键词Cooperative Path Following Marine Surface Vehicles Neural Networks Observer Uncertainties
发表期刊International Journal of Systems Science
ISSN0020-7721
2016
卷号47期号:2页码:343–359
收录类别SCI ; EI
EI收录号20152600983026
WOS记录号WOS:000360553200006
产权排序1
资助机构National Nature ScienceFoundation of China [grant number 61273137], [grant number51209026] ; the China Postdoctoral Science Foundation [grantnumber 2015M570247] ; the Scientific Research Fund of LiaoningProvincial Education Department [grant number L2013202] ; and the Fundamental Research Funds for the Central Universities[grant number 3132015021], [grant number 3132014321].
摘要This paper addresses the cooperative path-following problem of multiple marine surface vehicles subject to dynamical uncertainties and ocean disturbances induced by unknown wind, wave and ocean current. The control design falls neatly into two parts. One is to steer individual marine surface vehicle to track a predefined path and the other is to synchronise the along-path speed and path variables under the constraints of an underlying communication network. Within these two formulations, a robust adaptive path-following controller is first designed for individual vehicles based on backstepping and neural network techniques. Then, a decentralised synchronisation control law is derived by means of consensus on along-path speed and path variables based on graph theory. The distinct feature of this design lies in that synchronised path following can be reached for any undirected connected communication graphs without accurate knowledge of the model. This result is further extended to the output feedback case, where an observer-based cooperative path-following controller is developed without measuring the velocity of each vehicle. For both designs, rigorous theoretical analysis demonstrate that all signals in the closed-loop system are semi-global uniformly ultimately bounded. Simulation results validate the performance and robustness improvement of the proposed strategy.
语种英语
WOS标题词Science & Technology ; Technology
WOS类目Automation & Control Systems ; Computer Science, Theory & Methods ; Operations Research & Management Science
关键词[WOS]UNCERTAIN NONLINEAR-SYSTEMS ; MODEL UNCERTAINTY ; VESSELS ; TRACKING ; FORM
WOS研究方向Automation & Control Systems ; Computer Science ; Operations Research & Management Science
引用统计
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/16466
专题水下机器人研究室
通讯作者Wang D(王丹)
作者单位1.Marine Engineering College, Dalian Maritime University, Dalian, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
推荐引用方式
GB/T 7714
Wang H,Wang D,Peng ZH. Adaptive neural control for cooperative path following of marine surface vehicles: state and output feedback[J]. International Journal of Systems Science,2016,47(2):343–359.
APA Wang H,Wang D,&Peng ZH.(2016).Adaptive neural control for cooperative path following of marine surface vehicles: state and output feedback.International Journal of Systems Science,47(2),343–359.
MLA Wang H,et al."Adaptive neural control for cooperative path following of marine surface vehicles: state and output feedback".International Journal of Systems Science 47.2(2016):343–359.
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