2021/06/11 by Lulu Pan, Pan, Lulu, Haibin Shao +5 · 2 citations
Computer Science · Engineering · Mathematics · #Artificial intelligence #Computer science #Consensus #Control (management) #Control theory (sociology) #Decentralised system #Distributed Control Multi-Agent Systems #Distributed computing #Event (particle physics) #FOS: Computer and information sciences #FOS: Electrical engineering #Mathematics #Matrix (chemical analysis) #Multi-agent system #Multiagent Systems (cs.MA) #Neural Networks Stability and Synchronization #Opportunistic and Delay-Tolerant Networks #Scalar (mathematics) #Sequence (biology) #Systems and Control (eess.SY) #cs.MA #cs.SY #eess.SY #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2106.06198
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2021/06/11 · openalex created_date 2021/06/22 · arxiv created 2022/09/05 · arxiv updated 2022/09/07 · openalex updated_date 2026/07/28
This paper examines the event-triggered consensus of the multi-agent system on matrix-weighted networks, where the interdependencies among higher-dimensional states of neighboring agents are characterized by matrix-weighted edges in the network. Specifically, a novel distributed dynamic event-triggered coordination strategy is proposed for this category of generalized networks, in which an auxiliary system is employed for each agent to dynamically adjust the triggering threshold, which plays an essential role in guaranteeing that the triggering time sequence does not exhibit Zeno behavior. Distributed event-triggered control protocols are proposed to guarantee leaderless and leader-follower consensus for multi-agent systems on matrix-weighted networks, respectively. Remarkably, the spectrum of matrix-valued weights is crucial in event-triggered mechanism design for matrix-weighted networks, generalizing those results only applicable for scalar-weighted networks. The proposed approach allows each agent to broadcast and receive information only at its triggering instants. Finally, simulation examples are provided to demonstrate the theoretical results.