LAUSR

This paper considers the distributed tracking problem for multiagent systems (MASs) under connected and undirected graphs. A distributed estimator is proposed and analyzed for every agent to estimate the states of a general class of targets with continuous-time nonlinear dynamics. The agents employ a distributed estimator that is designed for each agent based on its information and communication with their local neighbors in the network for estimating the states of the targets in the presence of noise. It is proved that using the proposed distributed estimator, the agents can exponentially estimate the states of the noisy nonlinear targets with ultimate bounded errors. Simulation results demonstrate the effectiveness of the proposed estimator.