基于一阶动力学模型的多智能体系统一致性

The Consensus of Multi-agents Based on First-order Dynamical Model

研究了带有权重边的无向图拓扑结构下的多智能体系统,提出了固定采样、事件触发和周期采样等策略来实现系统一致性。基于李雅普诺夫稳定性理论建立了数学模型,并进行了分析和仿真研究,结果表明:事件触发策略能成功消除系统中的芝诺行为,能确保在相应策略下实现多智能体系统一致性。

This study investigates multi-agent systems in weighted undirected graph topologies,addressing the consensus prob-lem through fixed-interval sampling,event-triggered,and periodic sampling strategies in such networks.Leveraging Lyapunov stability theory,a mathematical model has been established and thoroughly analyzed,along with simulation verification.The research reveals that the proposed event-triggered strategy eliminates Zeno behavior within the system,thereby ensuring con-sistent stability.Designed simulation experiments validate that multi-agent systems effectively achieve consensus under the corresponding strategies.