A GENERAL FRAMEWORK FOR CONSENSUS NETWORKS

Abstract

A new framework for the analysis of consensus networks is developed. The theory consists of necessary and sufficient conditions and it is flexible enough to comprise a variety of consensus systems. Under mild connectivity assumptions, the discussion ranges from linear, nonlinear, ordinary, functional and leader-follower models. The establishment of explicit estimates on the rate of convergence is the central objective. Our work extends and unifies past related works in the literature. Illustrative examples and simulations are presented to outline the theoretical results.