A probabilistic analysis of the average consensus algorithm with quantized communication

Abstract

In the average consensus problem the states of a set of agents, linked according to a directed graph, have to be driven to their average. When the communication between neighbors is uniformly quantized, such a problem can not be exactly solved by a linear time-invariant algorithm. In this work, we propose a probabilistic estimate of the error from the agreement, in terms of the eigenvalues of the evolution matrix describing the algorithm.