Distributed Dynamic Clustering and Consensus in Multiagent Systems

• 成果类型: Article
• 署名作者: Lian, Bosen; Koru, Ahmet Taha; Xue, Wenqian; Lewis, Frank L.; Davoudi, Ali
• 署名单位: Auburn University System; Auburn University; State University System of Florida; University of Florida
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3385349
• 发表日期: 2024
• 页码: 6474-6481
• 关键词: Clustering methods; TOPOLOGY; Directed graphs; Real-time systems; Multi-agent systems; Consensus control; trajectory; Cluster consensus; distributed formation; dynamic clustering; graph theory

摘要

This article proposes a unified framework of a distributed dynamic clustering method and a distributed control law to solve the cluster consensus problem for networked multiagent systems (MASs) with multiple leaders. Given any initial unclustered directed graph and any initial-state followers and leaders, the distributed dynamic clustering method aims to cluster each leader with at least one follower without interconnection among the clusters. This cuts some initially available edges online by considering the real-time local information of states and connections while the distributed consensus control law is running. Then, the unified framework solves the problem under mild assumptions such that all agents in the same cluster reach a consensus with the leader without interference from the other clusters. The proposed method is validated in simulation examples.