NDLI: Robust Consensus of Multi-agent Systems with Noise

Content Provider	IEEE Xplore Digital Library
Author	Wang Lin Liu Zhixin Guo Lei
Copyright Year	2007
Description	Author affiliation: Chinese Acad. of Sci., Beijing (Wang Lin; Liu Zhixin; Guo Lei)
Abstract	The consensus problem of multi-agent systems has attracted wide attention from researchers in recent years, following the initial work of Jadbabaie et al [1] on the analysis of a simplified Vicsek model. While the original Vicsek model contains noise effects, almost all the existing theoretical results on consensus problem, however, do not take the noise effects into account. The purpose of this paper is to initiate a study of the consensus problems under noise disturbances. First, the class of multi-agent systems under study is transformed into the following general time-varying systems with noises: x(t+1) = P(t)x(t)+w(t+1), where {P(t)} is a sequence of nonnegative stochastic matrices. Then, for such a general time-varying systems, the equivalent relationships are established among (i) robust consensus, (ii) the positivity of the second smallest eigenvalue of a weighted Laplacian matrix, and (iii) the joint connectivity of the associated dynamical neighbor graphs. Finally, this basic equivalence result is shown to be applicable to several class of concrete multi-agent models with noises.
Starting Page	737
Ending Page	741
File Size	243200
Page Count	5
File Format	PDF
ISBN	9787811240559
DOI	10.1109/CHICC.2006.4347503
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	stochastic matrix Multiagent systems Laplace equations Robust stability graph theory Graph theory robust consensus Time-varying systems exponential stability Robust control Vicsek model Time varying systems Stochastic systems Stochastic resonance connectivity Eigenvalues and eigenfunctions Laplacian matrix Noise robustness
Content Type	Text
Resource Type	Article

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