Distributed Average Tracking for Multiple Signals Generated by Linear Dynamical Systems: An Edge-based Framework

摘要

This paper studies the distributed average tracking problem for multipletime-varying signals generated by linear dynamics, whose reference inputs arenonzero and not available to any agent in the network. In the edge-basedframework, a pair of continuous algorithms with, respectively, static andadaptive coupling strengths are designed. Based on the boundary layer concept,the proposed continuous algorithm with static coupling strengths canasymptotically track the average of multiple reference signals without thechattering phenomenon. Furthermore, for the case of algorithms with adaptivecoupling strengths, average tracking errors are uniformly ultimately boundedand exponentially converge to a small adjustable bounded set. Finally, asimulation example is presented to show the validity of theoretical results.