Convergence speed in distributed consensus over dynamically switching random networks☆ Export

@article{Zhou_09, 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.}, author = {Zhou, Jing and Wang, Qian}, citeulike-article-id = {4503890}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.automatica.2009.01.021}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S000510980900051X}, day = {18}, doi = {10.1016/j.automatica.2009.01.021}, issn = {00051098}, journal = {Automatica}, keywords = {consensus, convergence\_rate, distributed\_control, random\_graphs}, month = {March}, posted-at = {2009-05-12 04:05:56}, priority = {2}, title = {Convergence speed in distributed consensus over dynamically switching random networks☆}, url = {http://dx.doi.org/10.1016/j.automatica.2009.01.021}, year = {2009} }

TY - JOUR ID - Zhou_09 L3 - citeulike-article-id:4503890 N2 - 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. JF - Automatica SN - 00051098 TI - Convergence speed in distributed consensus over dynamically switching random networks☆ KW - consensus KW - convergence_rate KW - distributed_control KW - random_graphs AU - Zhou, Jing AU - Wang, Qian PY - 2009/03/18/ UR - http://dx.doi.org/10.1016/j.automatica.2009.01.021 ER -