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组合连通拓扑下基于事件触发的多智能体快速一致性算法

陈世明 管俊杰 高彦丽 裴惠琴 邱昀

陈世明, 管俊杰, 高彦丽, 裴惠琴, 邱昀. 组合连通拓扑下基于事件触发的多智能体快速一致性算法. 自动化学报, 2018, 44(12): 2269-2277. doi: 10.16383/j.aas.2018.c160839
引用本文: 陈世明, 管俊杰, 高彦丽, 裴惠琴, 邱昀. 组合连通拓扑下基于事件触发的多智能体快速一致性算法. 自动化学报, 2018, 44(12): 2269-2277. doi: 10.16383/j.aas.2018.c160839
CHEN Shi-Ming, GUAN Jun-Jie, GAO Yan-Li, PEI Hui-Qin, QIU Yun. Event-triggered Fast Consensus Algorithm for Multi-agent Systems Under Jointly-connected Topology. ACTA AUTOMATICA SINICA, 2018, 44(12): 2269-2277. doi: 10.16383/j.aas.2018.c160839
Citation: CHEN Shi-Ming, GUAN Jun-Jie, GAO Yan-Li, PEI Hui-Qin, QIU Yun. Event-triggered Fast Consensus Algorithm for Multi-agent Systems Under Jointly-connected Topology. ACTA AUTOMATICA SINICA, 2018, 44(12): 2269-2277. doi: 10.16383/j.aas.2018.c160839

组合连通拓扑下基于事件触发的多智能体快速一致性算法

doi: 10.16383/j.aas.2018.c160839
基金项目: 

国家自然科学基金 11662002

国家自然科学基金 61364017

江西省科技厅项目 20165BCB190 11

江西省科技厅项目 20171BAB202029

江西省教育厅项目 GJJ151168

江西省科技厅项目 20161BBE53008

详细信息
    作者简介:

    管俊杰   华东交通大学电气与自动化工程学院硕士研究生.2015年获得湖南工业大学学士学位.主要研究方向为多智能体系统协调控制.E-mail:junjieguan@163.com

    高彦丽   华东交通大学电气与自动化工程学院副教授.主要研究方向为工业过程参数检测, 复杂网络安全及控制.E-mail:selina@ecjtu.jx.cn

    裴惠琴   华东交通大学电气与自动化工程学院博士研究生.2010年获得华东交通大学控制理论与控制工程硕士学位.主要研究方向为群体动力学与协调控制.E-mail:peihuiqinnx@126.com

    邱昀  华东交通大学电气与自动化工程学院硕士研究生.主要研究方向为多智能体系统协调控制.E-mail:qiuyun1004@163.com

    通讯作者:

    陈世明   华东交通大学电气与自动化工程学院教授.2006年获得华中科技大学博士学位.主要研究方向为复杂网络理论及应用, 多智能体系统协调控制, 粒子群优化算法.本文通信作者.E-mail:shmchen@ecjtu.jx.cn

Event-triggered Fast Consensus Algorithm for Multi-agent Systems Under Jointly-connected Topology

Funds: 

National Natural Science Foundation of China 11662002

National Natural Science Foundation of China 61364017

Project of Science and Technology Department of Jiangxi Province 20165BCB190 11

Project of Science and Technology Department of Jiangxi Province 20171BAB202029

Project of Education Department of Jiangxi Province GJJ151168

Project of Science and Technology Department of Jiangxi Province 20161BBE53008

More Information
    Author Bio:

       Master student at the School of Electrical and Automation Engineering, East China Jiaotong University. He received his bachelor degree from Hunan University of Technology in 2015. His research interest covers coordination control of multi-agent systems

      Associate professor at the School of Electrical Engineering and Automation, East China Jiaotong University. Her research interest covers industrial process parameter detection, safety and control of complex networks

       Ph. D. candidate at the School of Electrical and Automation Engineering, East China Jiaotong University. She received her master degree in control theory and control engineering from East China Jiaotong University in 2010. Her research interest covers swarm dynamics and cooperative control

       Master student at the School of Electrical and Automation Engineering, East China Jiaotong University. His research interest covers coordination control of multi-agent systems

    Corresponding author: CHEN Shi-Ming   Professor at the School of Electrical and Automation Engineering, East China Jiaotong University. He received his Ph. D. degree from Huazhong University of Science and Technology in 2006. His research interest covers complex network theory and application, coordination control of multi-agent systems, and particle swarm optimization (PSO) algorithm. Corresponding author of this paper
  • 摘要: 针对组合连通拓扑下多智能体系统控制过程中存在通信和计算资源损耗大以及系统收敛速度慢等问题,提出一种新的具有状态预测器的事件触发一致性控制协议,通过设计状态预测器使每个智能体都能对其邻居智能体的未来状态作出预测;同时,对于智能个体给出了基于状态信息的事件触发条件,当状态误差满足该条件才触发事件.在该控制策略下多智能体系统可在节约通信和计算资源的同时具有更快的收敛速度.利用Lyapunov稳定性理论和代数图论,证明了所提事件触发控制策略能够有效实现组合连通拓扑结构下的平均一致性,且不存在Zeno行为.仿真实例进一步验证了理论结果的有效性.
    1)  本文责任编委 吕金虎
  • 图  1  拓扑图

    Fig.  1  Topological graph

    图  2  $\tau =0.5$ s时, 三种控制策略下的状态轨迹

    Fig.  2  The state trajectory under three kinds of\\ control scheme when $\tau =0.5$ s

    图  3  $\tau =0.5$ s时三种控制策略下的分歧向量范数$\left\| {\delta (t)} \right\|$

    Fig.  3  The Euclidean norm of disagreement vector $\left\| {\delta (t)} \right\|$ under three kinds of control scheme when $\tau =0.5$ s

    图  4  有无状态预测控制策略下状态轨迹对比图

    Fig.  4  The comparison diagram between predictive control scheme and common control scheme

    图  5  $\tau =0.5$ s每个智能体在控制策略(7)下触发间隔

    Fig.  5  The triggered interval of each agent under control scheme (7)

    表  1  事件条件(7), (9)和(10)下平均触发间隔

    Table  1  The average triggered interval under event conditions (7), (9) and (10)

    拓扑切换事件条件(s)
    周期(s)式(7)式(9)式(10)
    0.40.95630.67420.7892
    0.51.08770.72090.9461
    0.61.10270.80571.0673
    下载: 导出CSV
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出版历程
  • 收稿日期:  2016-12-26
  • 录用日期:  2017-04-07
  • 刊出日期:  2018-12-20

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