Output consensus for networks of non-identical introspective agents

Abstract

In this paper, we consider three problems, namely, the output consensus problem, the model-reference output consensus problem, and the regulation of output consensus problem, for a network of non-identical right-invertible linear agents. The network provides each agent with a linear combination of multiple agents' outputs. We assume that all the agents are introspective, meaning that they have access to their own local measurements. Under this assumption, we then propose a distributed linear protocol to solve each problem for a broad class of network topologies, including not only Laplacian topologies for a directed graph which contains a directed spanning tree, but a wide family of asymmetric topologies.