Characterizing convergence speed for consensus seeking over dynamically switching directed random networks

Authors:
Jing Zhou;Qian Wang
Affiliations:
Mechanical Engineering, Penn State University, PA;Mechanical Engineering, Penn State University, PA
Venue:
ACC'09 Proceedings of the 2009 conference on American Control Conference
Year:
2009

Citing 3
Cited 0

Matrix analysis

Matrix analysis
Active Fault Tolerant Control Systems: Stochastic Analysis and Synthesis

Active Fault Tolerant Control Systems: Stochastic Analysis and Synthesis
Reaching a Consensus in a Dynamically Changing Environment: Convergence Rates, Measurement Delays, and Asynchronous Events

SIAM Journal on Control and Optimization

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Abstract

Characterizing convergence speed is one of the 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 directed random network. Each link in the network, which represents the directed information flow between any ordered pair of agents, could be subject to failure with certain probability. Hence we model the information flow using dynamic random digraphs. 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 per-step (mean square) convergence factor as a measure of the convergence speed and derive the exact value for this factor. Numerical examples are also given to illustrate our theoretical results.