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Adaptive consensus protocol for networks of multiple agents with nonlinear dynamics using neural networks
Author(s) -
Liu Yang,
Jia Yingmin
Publication year - 2012
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.427
Subject(s) - nonlinear system , protocol (science) , multi agent system , consensus , invariance principle , artificial neural network , computer science , control theory (sociology) , transient (computer programming) , graph , protocol design , artificial intelligence , control (management) , theoretical computer science , communications protocol , computer network , medicine , linguistics , philosophy , physics , alternative medicine , pathology , quantum mechanics , operating system
In this paper, an adaptive protocol is proposed to solve the consensus problem of multi‐agent systems with high‐order nonlinear dynamics by using neural networks (NNs) to approximate the unknown nonlinear system functions. It is derived that all agents achieve consensus if the undirected interaction graph is connected, and the transient performance of the multi‐agent system is also investigated. It shows that the adaptive protocol and the consensus analysis can be easily extended to switching networks by the existing LaSalle's Invariance Principle of switched systems. A numerical simulation illustrates the effectiveness of the proposed consensus protocol. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society