Stochastic Consensus over Time-Varying Networks of Linear Symmetric Agents

抄録

Multi-agent systems over noisy networks with linear symmetric agents are considered. The topology of the network which defines the availability of communication among the agents is assumed to be a directed, weakly connected and balanced graph or an undirected and connected one. Furthermore, the communication graph is allowed to be time varying. The aim of this study is to establish a stochastic averaging consensus algorithm under a noisy environment for each time-varying network. The convergence analysis of the proposed algorithms reveals an explicit relation between the number of iterations and the closeness of the agreement, which gives a stopping rule for the consensus algorithm. The results are illustrated through numerical examples.