Consensus in Networked Multiagent Systems With Stochastic Sampling

This brief addresses the consensus problem in networks with stochastic sampling, assuming that the sampling intervals are independently and identically distributed. Necessary and sufficient conditions to guarantee mean square consensus of both first-order and second-order multiagent systems are derived in terms of statistical properties of the sampling intervals. Numerical examples are also given to verify the theoretical results, revealing that the conditions on the sampling intervals are significantly relaxed in contrast to the previous sufficient conditions. By applying the first-order model to opinion consensus problems with intermittent interactions, it is finally found that the temporal heterogeneity of human activities impedes the opinion consensus forming.