Average-consensus Tracking for First-order Multi-agent Systems Based on Sampled Data

Abstract

Average-consensus tracking problem of first-order multi-agent systems is investigated in this paper, and a consensus algorithm under sampled data is proposed for two cases, one of which is that all the agents access constant reference inputs and the other is that some agents have the constant reference inputs but the left has no reference inputs. Based on matrix theory and frequency-domain analysis, consensus conditions are obtained for the agents under two cases converging to the average consensus asymptotically with the strongly connected and balanced topology and the symmetric and connected topology. Finally, numerical simulation examples are given to illustrate the effectiveness of the proposed sampled-data control strategy.