Adaptive consensus protocol for networks of multiple agents with nonlinear dynamics using neural networks |
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| Authors: | Yang Liu Yingmin Jia |
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| Affiliation: | 1. Seventh Research Division and the Department of Systems and Control, Beihang University (BUAA), Beijing 100191, China;2. Key Laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Ministry of Education, SMSS, Beihang University (BUAA), Beijing 100191, China |
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| Abstract: | 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 |
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| Keywords: | Multi‐agent system nonlinear dynamics neural network (NN) adaptive consensus protocol |
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