Clustering in diffusively coupled networks

  • Weiguo Xia*
  • , Ming Cao
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

243 Citations (Scopus)
131 Downloads (Pure)

Abstract

This paper shows how different mechanisms may lead to clustering behavior in connected networks consisting of diffusively coupled agents. In contrast to the widely studied synchronization processes, in which the states of all the coupled agents converge to the same value asymptotically, in the cluster synchronization problem studied in this paper, we require all the interconnected agents to evolve into several clusters and each agent only to synchronize within its cluster. The first mechanism is that agents have different self-dynamics, and those agents having the same self-dynamics may evolve into the same cluster. When the agents' self-dynamics are identical, we present two other mechanisms under which cluster synchronization might be achieved. One is the presence of delays and the other is the existence of both positive and negative couplings between the agents. Some sufficient and/or necessary conditions are constructed to guarantee n-cluster synchronization. Simulation results are presented to illustrate the effectiveness of the theoretical analysis. (C) 2011 Elsevier Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)2395-2405
Number of pages11
JournalAutomatica
Volume47
Issue number11
DOIs
Publication statusPublished - Nov-2011

Keywords

  • Synchronization
  • Clustering
  • Diffusive coupling
  • Self-dynamics
  • Time delay
  • Negative coupling weights
  • SYNCHRONIZATION ANALYSIS
  • MULTIAGENT SYSTEMS
  • NEURAL-NETWORKS
  • CONSENSUS

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