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Publication
IEEE TACON
Paper
Synchronization and convergence of linear dynamics in random directed networks
Abstract
Recently, methods in stochastic control are used to study the synchronization properties of a nonautonomous discrete-time linear system x(k + 1) = G(k)x(k) where the matrices G(k) are derived from a random graph process. The purpose of this note is to extend this analysis to directed graphs and more general random graph processes. Rather than using Lyapunov type methods, we use results from the theory of inhomogeneous Markov chains in our analysis. These results have been used successfully in deterministic consensus problems and we show that they are useful for these problems as well. Sufficient conditions are derived that depend on the types of graphs that have nonvanishing probabilities. For instance, if a scrambling graph occurs with nonzero probability, then the system synchronizes. © 2006 IEEE.