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作 者:Qinglai Wei Xin Wang Xiangnan Zhong Naiqi Wu
机构地区:[1]the State Key Laboratory for Management and Control of Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190 [2]the School of Artificial Intelligence,University of Chinese Academy of Sciences,Beijing 100049,and also with Qingdao Academy of Intelligent Industries,Qingdao 266109,China [3]the Department of Computer and Electrical Engineering and Computer Science,Florida Atlantic University,Boca Raton FL,33431 USA [4]the Institute of Systems Engineering,and Collaborative Laboratory for Intelligent Science and Systems,Macao University of Science and Technology,Macao 999078,China
出 处:《IEEE/CAA Journal of Automatica Sinica》2021年第2期423-431,共9页自动化学报(英文版)
基 金:supported in part by the National Natural Science Foundation of China(61722312,61533017,62073321);the National Key Research and Development Program of China(2018YFB1702300)。
摘 要:This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown motion.Its main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic noise.In traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent agents.By introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local interaction.Through the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is analyzed.Two simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.
关 键 词:Consensus control directed topology external disturbance multi-agent(MA)systems
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