Distributed Constrained Optimal Formation Matching for Large-Scale Systems

• 成果类型: Article
• 署名作者: Wu, Bofan; Peng, Zhaoxia; Wen, Guoguang; Huang, Tingwen; Rahmani, Ahmed
• 署名单位: Beihang University; Beijing Jiaotong University; Texas A&M University System; Texas A&M University College Station; Universite de Lille; Centrale Lille; Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Information Sciences & Technologies (INS2I)
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2023.3342067
• 发表日期: 2024
• 页码: 3457-3464
• 关键词: Multi-agent systems; large-scale systems; optimal matching; COSTS; cost function; bipartite graph; Search problems; Distributed constrained optimal formation matching problem; large-scale multiagent systems; unmatched phenomenon

摘要

In this article, we investigate a distributed constrained optimal formation matching problem for a large-scale multiagent system. A distributed formation matching algorithm for a large-scale multiagent system (DFMA-LSMAS) is proposed. The algorithm employs a distributed continuous-time strategy to deal with a minimal weight bipartite graph matching problem for the optimal matching relationship between each agent and each hole in the formation configuration. It prevents a centralized structure and the explosion of storage spaces compared with the Kuhn-Munkras algorithm. Additionally, DFMA-LSMAS utilizes a distributed parameter projection approach for the optimal location of the formation configuration subjected to a common state constraint. It reduces the growth of the auxiliary variables with the scale of the multiagent system. In the special case, an unmatched phenomenon appears which may cause the failure of DFMA-LSMAS. Therefore, a perturbation-based algorithm is provided to eliminate the influence of this phenomenon, but does not affect the optimality of the solution. Finally, simulation results are provided to verify the algorithms.