Consensus Analysis and Convergence Rate Optimization for Open Multiagent Systems
研究了开放多智能体系统中智能体随机加入或离开网络时的快速共识问题，分析了切换频率和非连通持续时间的影响，提出了共识条件和收敛速率优化方案。
This article investigates the fast consensus problem in open multiagent systems (OMASs), where agents can randomly join or leave the network. Such dynamic behaviors significantly impact system consensus and its convergence rates. To address these challenges, we analyze both the frequency of agent switching and the duration during which the network remains nonconnected. A consensus condition for OMAS with time-varying network topology is derived, and explicit upper bounds on switching frequency and dwell time are established to guarantee consensus. To further achieve fast consensus, a convergence rate optimization scheme is proposed, along with a distributed implementation based on the alternating direction method of multiplier. Extensive simulations demonstrate the effectiveness and superiority of the proposed control strategy compared to existing OMAS consensus approaches.