Distributed average tracking for multiple signals with linear dynamics: An edge-based framework

This paper studies the distributed average tracking problem for multiple time-varying signals with general linear dynamics, whose reference inputs are nonzero and not available to any agents in networks. In distributed fashion, a pair of discontinuous algorithms with, respectively, static and adaptive coupling strengths are designed. Based on the relative information among the neighboring agents, the states of each agent will converge to the average of the multiple reference signals if the communication topology is undirected and connected. Furthermore, sufficient conditions for the existence of the distributed algorithms are given if each agent is stabilizable. The value of consensus manifold in multi-agent systems can also be obtained in this paper. Finally, simulation examples are presented to show the validity of the theoretical results.