Litcius/Paper detail

Saturated Sampled-Data Distributed Control for Interval Consensus of Multi-Agent Systems

Yao Zou, Zongyu Zuo, Kewei Xia, Michael Basin

2022IEEE Transactions on Signal and Information Processing over Networks13 citationsDOI

Abstract

This paper studies the interval consensus of multi-agent systems using sampled data. Specifically, all the agents come to a consensus inside a given interval, which is only available to a portion of agents. The network is characterized by a strongly connected directed topology. By considering generic saturations with heterogeneity and asymmetry, two sampled-data distributed control protocols are proposed, which allow asynchronous sampling such that a global clock synchronization mechanism is not required. To be specific, with the delivery of the interval projection information, a saturated sampled-data distributed control protocol is first proposed. Accompanied by it, a selection criterion for sampling periods is built to achieve the interval consensus. Next, by narrowing down possible input options to three, another sampled-data distributed control protocol with ternary input options is proposed. A proper excitation mechanism is designed such that the interval consensus objective is achieved without strict requirements on the sampling periods. Simulation examples are taken to verify the established theoretical results.

Topics & Concepts

Interval (graph theory)Computer scienceAsynchronous communicationProtocol (science)Sampling (signal processing)Synchronization (alternating current)ConsensusMulti-agent systemControl (management)Distributed computingControl theory (sociology)MathematicsComputer networkChannel (broadcasting)Artificial intelligenceCombinatoricsMedicineAlternative medicineComputer visionFilter (signal processing)PathologyDistributed Control Multi-Agent SystemsAdvanced Memory and Neural ComputingNeural Networks Stability and Synchronization