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Leader-follower cooperative control of multiple marine surface vehicles with unknown disturbances  ( EI收录)   被引量:18

文献类型:期刊文献

英文题名:Leader-follower cooperative control of multiple marine surface vehicles with unknown disturbances

作者:Chen, GuangJun[1]; Liu, HaiTao[1]

机构:[1] Guangdong Ocean University, School of Mechanical and Power Engineering, Zhanjiang, 524088, China

年份:2019

起止页码:5743

外文期刊名:Proceedings - 2019 Chinese Automation Congress, CAC 2019

收录:EI(收录号:20201008253768)

基金:ACKNOWLEDGMENT This work was supported by the Natural Science Foundation of Guangdong Province in China [grant number 2018A0303130076], the 2019 "Chong First-class" Provincial Financial Special Funds Construction Project [grant number 231419019], the Science and Technology Planning Project of Zhanjiang City [grant number 2017A02025], the Fostering Plan for Major Scientific Research Projects of Education Department of Guangdong Province-Characteristic Innovation Projects (grant number 2017KTSCX087 ), and the Guangdong Science and Technology Project (grant number 2013B011304009).

语种:英文

外文关键词:Graph theory - Vehicle to vehicle communications - Cooperative communication - Numerical methods - Backstepping - Closed loop systems - Vehicles

外文摘要:This article investigates the leader-follower cooperative control of multiple marine surface vehicles with unknown disturbances induced ocean environment. A nonlinear observer is developed to estimate unknown time-varying disturbances, and a rapid convergent cooperative controller is designed based on graph theory, backstepping technology and disturbance observer. The results show that the proposed cooperative controllers can achievement formation behavior control among vehicle for inaccurate dynamics model and any undirected connected communication topology of each vehicle. By using Lyapunov stability analysis, all signals of closed-loop systems are guaranteed to be uniformly ultimately bounded, and the tracking errors eventually tend to zero. Numerical simulation studies are demonstrated the effectiveness of the proposed methods. ? 2019 IEEE.

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