Distributed average tracking of linear differential inclusions

In this paper, we study the distributed average tracking problem for a multi-agent system with the linear differential inclusions dynamics. Unlike the existing distributed average tracking algorithms for multi-agent systems in which all agents are assumed to have certain dynamics, we allow the dynamics to be uncertain for all agents. This paper proposes a distributed algorithm based on nonsmooth feedback. The convergence results rely on the input-to-state stability properties of the underling system and the properties of composite Laplacian quadratics. We show that if the reference signals and their control inputs are bounded, then the average tracking problem can be solved.