Brief paper: Convergence speed in distributed consensus over dynamically switching random networks

  • Authors:
  • Jing Zhou;Qian Wang

  • Affiliations:
  • Department of Mechanical and Nuclear Engineering, the Pennsylvania State University, University Park, PA 16802, United States;Department of Mechanical and Nuclear Engineering, the Pennsylvania State University, University Park, PA 16802, United States

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2009

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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.