引用本文: | 马小陆,谭毅波,梅宏,房建兵.切换拓扑下事件触发多智能体系统预定时间一致性[J].控制理论与应用,2025,42(2):373~384.[点击复制] |
MA Xiao-lu,TAN Yi-bo,MEI Hong,FANG Jian-bing.Event-triggered predefined-time consensus control of multi-agent systems under switching topologies[J].Control Theory and Technology,2025,42(2):373~384.[点击复制] |
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切换拓扑下事件触发多智能体系统预定时间一致性 |
Event-triggered predefined-time consensus control of multi-agent systems under switching topologies |
摘要点击 3498 全文点击 32 投稿时间:2022-09-07 修订日期:2024-12-13 |
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DOI编号 10.7641/CTA.2024.20791 |
2025,42(2):373-384 |
中文关键词 多智能体系统 预定时间一致性 事件触发 切换拓扑 分布式控制 |
英文关键词 multi-agent systems predefined-time consensus event-triggered switching topologies distributed control |
基金项目 国家自然科学基金资助项目(61472282, 62172004, 62072002), 安徽省科技重大专项项目(202003a05020028), 安徽高校自然科学研究重点项目 (KJ2019A0065), 安徽省重点研究开发计划项目(202004a0502001), 特种重载机器人安徽省重点实验室开放课题(TZJQR004–2020)资助. |
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中文摘要 |
本文研究了具有非线性不确定性的多智能体系统在切换拓扑下的预定时间一致性问题, 提出了基于事件 触发的分布式预定时间一致性控制算法. 该算法在节约资源的情况下, 可使系统在预设时间内实现一致. 通过代数 图论和Lyapunov理论证明系统的预定时间稳定性,且不存在Zeno行为. 仿真对比实验验证了所提算法的可行性和 有效性. 相较于有限时间控制算法, 本算法的收敛时间界与初始状态无关, 可通过选择单一时间参数设定系统收敛时间上界; 相较于固定时间控制算法, 本算法的预设收敛时间与控制算法参数无关, 设定简单, 且预估收敛时间具有 更低的保守性. |
英文摘要 |
This paper studies the problem of predefined-time consensus for multi-agent systems with nonlinear uncertainties under switching topologies and proposes an event-triggered distributed predefined-time consensus control algorithm. This algorithm enables the multi-agent system consensus in predefined time with limited resources. The predetermined time stability of the system is proved by the algebraic graph theory and the Lyapunov theory, and there is no Zeno behavior. Simulation comparison experiments verify the feasibility and effectiveness of the proposed algorithm. Compared with the finite-time control algorithm, the upper bound of the system convergence time of the proposed algorithm is independent of the initial conditions, and it can be specified by choosing a time parameter. Compared with the fixed-time control algorithm, the preset convergence time of this algorithm is independent of the control algorithm parameters, which is simple to set, and the estimated convergence time is less conservative. |
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