Bridging the Gap Between Transmission Noise and Sampled Data for Robust Consensus of Multi-Agent Systems

It is well known that multi-agent systems (MASs) are ubiquitous in natural and artificial systems. This paper aims at bridging the gap between transmission noise and sampled data for robust consensus of MASs. In detail, we have developed a theoretical framework for analyzing the robust consensus of MASs with sampled-data controllers and transmission noises. Using the delay-input and discretization approaches, we obtain two sufficient conditions on the existence of sampling periods and controller parameters for robust consensus of MASs, respectively. In particular, we deduce the estimates of the convergence speeds of consensus errors for the above two methods. Finally, numerical simulations are also given to validate our theoretical results.