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IEEE transaction on neural networks and learning systems, 2016-01, Vol.27 (1), p.178-189
2016

Details

Autor(en) / Beteiligte
Titel
Convergence Rate for Discrete-Time Multiagent Systems With Time-Varying Delays and General Coupling Coefficients
Ist Teil von
  • IEEE transaction on neural networks and learning systems, 2016-01, Vol.27 (1), p.178-189
Ort / Verlag
United States: IEEE
Erscheinungsjahr
2016
Link zum Volltext
Quelle
IEL
Beschreibungen/Notizen
  • Multiagent systems (MASs) are ubiquitous in our real world. There is an increasing attention focusing on the consensus (or synchronization) problem of MASs over the past decade. Although there are numerous results reported on the convergence of a discrete-time MAS based on the infinite products of matrices, few results are on the convergence rate. Because of the switching topology, the traditional eigenvalue analysis and the Lyapunov function methods are both invalid for the convergence rate analysis of an MAS with a switching topology. Therefore, the estimation of the convergence rate for a discrete-time MAS with time-varying delays remains a difficult problem. To overcome the essential difficulty of switching topology, this paper aims at developing a contractive-set approach to analyze the convergence rate of a discrete-time MAS in the presence of time-varying delays and generalized coupling coefficients. Using the proposed approach, we obtain an upper bound of the convergence rate under the condition of joint connectivity. In particular, the proposed method neither requires the nonnegative property of the coupling coefficients nor the basic assumption of a uniform lower bound for all positive coupling coefficients, which have been widely applied in the existing works on this topic. As an application of the main results, we will show that the classical Vicsek model with time delays can realize synchronization if the initial topology is connected.
Sprache
Englisch
Identifikatoren
ISSN: 2162-237X
eISSN: 2162-2388
DOI: 10.1109/TNNLS.2015.2473690
Titel-ID: cdi_crossref_primary_10_1109_TNNLS_2015_2473690

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