Consensus of Linear Multi-Agent Systems in the Presence of Bounded Measurement Noises

In this paper, we investigate the static epsilon-consensus problem of linear multi-agent systems in the presence of bounded noises in the measurements of neighbors' states over a connected undirected communication topology. We propose two types of consensus protocols, one using full state measurements of the neighbors and the other using partial state measurements of the neighbors. With the knowledge of the noise bounds, we show that, under these consensus protocols, the agents achieve static epsilon-consensus. A numerical example is presented to illustrate the theoretical results.