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Distributed node‐to‐node consensus of multi‐agent systems with stochastic sampling
Author(s) -
Wan Ying,
Wen Guanghui,
Cao Jinde,
Yu Wenwu
Publication year - 2015
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3302
Subject(s) - node (physics) , sampling (signal processing) , computer science , nonlinear system , network topology , control theory (sociology) , multi agent system , consensus , lyapunov function , mathematical optimization , state (computer science) , square (algebra) , topology (electrical circuits) , mathematics , algorithm , control (management) , engineering , artificial intelligence , computer network , physics , geometry , structural engineering , filter (signal processing) , quantum mechanics , combinatorics , computer vision
Summary This paper is concerned with the mean square node‐to‐node consensus tracking problem for multi‐agent systems with nonidentical nonlinear dynamics and directed topologies. The randomly occurred uncertainties in the sampling devices may result in stochastically varied sampling periods, which lead to the investigation of node‐to‐node consensus problem under stochastic sampling. By employing the input‐delay method and discontinuous Lyapunov functional approach, it arrives at some sufficient conditions under which the state of each follower can track that of the corresponding leader asymptotically in the mean square sense. Finally, some numerical simulations are provided to verify the effectiveness of the theoretical results. Copyright © 2015 John Wiley & Sons, Ltd.