Sampled-Data Consensus for Multiple Double Integrators With Arbitrary Sampling

Abstract

This technical note studies the state consensus of multiple double integrators in a sampled-data setting with the assumption that the position-like states are the only detectable information transmitted over the network. Based on local information, it proposes a novel consensus protocol, under which each agent follows a closed-loop continuous-time dynamics between sampling instants. A necessary and sufficient condition and a sufficient condition are developed for the uniform and nonuniform data-sampling cases, respectively. Unlike the existing sampled-data consensus results, the presented protocol has the advantage of being applicable to the case with large sampling periods. Furthermore, the protocol parameters can be chosen independently of the network structures.