On consensus with a general discrete time convex combination based algorithm for multi-agent systems

A general convex combination based model in discrete time for the evolution of multi-agent systems is considered. Sufficient conditions under which an individual limit for each agent's state exists are subsequently derived. Moreover, it is shown that under stronger conditions, those individual limits are equal, i.e., consensus occurs. The relationship of these results to those of other well known consensus models is explained.