Convergence speed in distributed consensus over dynamically switching random networks

Jing Zhou, Qian Wang

Research output: Contribution to journalArticle

96 Citations (Scopus)

Abstract

Characterizing convergence speed is one of the most important research challenges in the design of distributed consensus algorithms for networked multi-agent systems. In this paper, we consider a group of agents that communicate via a dynamically switching random information network. Each link in the network, which represents the directed/undirected information flow between any ordered/unordered pair of agents, could be subject to failure with a certain probability. Hence we model the information flow using dynamically switching random graphs. We characterize the convergence speed for the distributed discrete-time consensus algorithm over a variety of random networks with arbitrary weights. In particular, we propose the asymptotic and per-step (mean square) convergence factors as measures of the convergence speed and derive the exact value for the per-step (mean square) convergence factor. Numerical examples are also given to illustrate our theoretical results.

Original languageEnglish (US)
Pages (from-to)1455-1461
Number of pages7
JournalAutomatica
Volume45
Issue number6
DOIs
StatePublished - Jun 1 2009

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Multi agent systems
Parallel algorithms

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

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Convergence speed in distributed consensus over dynamically switching random networks. / Zhou, Jing; Wang, Qian.

In: Automatica, Vol. 45, No. 6, 01.06.2009, p. 1455-1461.

Research output: Contribution to journalArticle

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