切换拓扑下动态事件触发多智能体系统固定时间一致性

孙梦薇; 任璐; 刘剑; 孙长银

doi:10.16383/j.aas.c211123

切换拓扑下动态事件触发多智能体系统固定时间一致性

doi: 10.16383/j.aas.c211123

孙梦薇^1,,
任璐^2,,
刘剑^3,,
孙长银^3,

1.
安徽大学物质科学与信息技术研究院合肥 230601
2.
安徽大学人工智能学院合肥 230601
3.
东南大学自动化学院南京 210018

基金项目: 国家自然科学基金 (61921004, 62103099, 62003044), 江苏省前沿引领技术基础研究专项 (BK20202006) 资助

详细信息

作者简介:
孙梦薇：安徽大学物质科学与信息技术研究院博士研究生. 主要研究方向为多智能体系统, 固定时间控制和事件触发控制. E-mail: q21101014@stu.ahu.edu.cn

任璐：安徽大学人工智能学院讲师. 2021年获得东南大学控制科学与工程博士学位. 主要研究方向为多智能体系统一致性控制, 复杂动态网络同步. 本文通信作者. E-mail: penny_lu@ahu.edu.cn

刘剑：东南大学自动化学院副研究员. 分别于2015年, 2020年获得北京科技大学学士和博士学位. 主要研究方向为多智能体系统, 非线性控制, 事件触发控制和固定时间控制. E-mail: bkliujian@163.com

孙长银：东南大学自动化学院教授. 1996年获得四川大学应用数学专业理学学士学位. 分别于2001年, 2004年获得东南大学电子工程专业硕士和博士学位. 主要研究方向为智能控制, 飞行器控制, 模式识别和优化理论. E-mail: cysun@seu.edu.cn

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出版历程
- 收稿日期: 2021-11-27
- 录用日期: 2022-03-01
- 网络出版日期: 2022-05-18
- 刊出日期: 2023-06-20

Dynamic Event-triggered Fixed-time Consensus Control of Multi-agent Systems Under Switching Topologies

1.
Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601
2.
School of Artificial Intelligence, Anhui University, Hefei 230601
3.
School of Automation, Southeast University, Nanjing 210018

Funds: Supported by National Natural Science Foundation of China (61921004, 62103099, 62003044) and Natural Science Foundation of Jiangsu Province of China (BK20202006)

More Information

Author Bio:
SUN Meng-Wei　Ph.D. candidate at the Institutes of Physical Science and Information Technology, Anhui University. Her research interest covers multi-agent systems, fixed-time control, and event-triggered control

REN Lu　Lecturer at the School of Artificial Intelligence, Anhui University. She received her Ph.D. degree in control science and engineering from Southeast University in 2021. Her research interest covers consensus control of multi-agent systems, and synchronization of complex dynamical networks. Corresponding author of this paper

LIU Jian　Associate professor at the School of Automation, Southeast University. He received his bachelor and Ph.D. degrees from University of Science and Technology Beijing in 2015 and 2020, respectively. His research interest covers multi-agent systems, nonlinear control, event-triggered control, and fixed-time control

SUN Chang-Yin　Professor at the School of Automation, Southeast University. He received his bachelor degree in applied mathematics from Sichuan University in 1996, and his master and Ph.D. degrees in electrical engineering from Southeast University in 2001 and 2004, respectively. His research interest covers intelligent control, flight control, pattern recognition, and optimal theory

摘要

摘要: 针对有扰动的一阶非线性多智能体系统在切换拓扑下的实际固定时间平均一致性问题, 提出了基于动态事件触发机制的固定时间一致性协议. 该一致性协议在节约更多资源的情况下, 使多智能体系统以更快的速度达到一致. 相对于有限时间一致性控制算法, 固定时间一致性控制算法的收敛时间不依赖于初始状态, 并且可以通过选择合适的控制器参数设定相应的收敛时间上界. 通过设计一个包含双曲正切函数的测量误差, 证明系统不存在Zeno行为. 由于内部动态变量的引入, 大量不必要的触发被取消, 从而节省能量损耗. 最后, 通过仿真实验验证算法的可行性和有效性.
- 多智能体系统 /
- 固定时间一致性 /
- 动态事件触发控制 /
- 切换拓扑
Abstract: This paper proposes a dynamic event-triggered fixed-time consensus protocol to address the practical fixed-time average consensus problems of first-order nonlinear multi-agent systems with external disturbances under switching topologies. This consensus protocol enables the multi-agent systems to reach consensus faster with limited resources. Compared with the finite-time consensus algorithm, the convergence time of the fixed-time consensus algorithm is independent of the initial conditions; and the upper bound of the convergence time can be specified by choosing appropriate controller parameters. By designing a measurement error involving hyperbolic tangent, we can prove that there is no Zeno behavior. Because of the introduction of an internal dynamic variable, massive unnecessary triggering instants are avoided to reduce energy consumption. Finally, simulation examples are provided to illustrate the feasibility and effectiveness of the theoretical results.
- Multi-agent systems /
- fixed-time consensus /
- dynamic event-triggered control /
- switching topologies

HTML全文

图 1 多智能体系统的切换拓扑

Fig. 1 Switching topologies of the multi-agent system

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图 2 多智能体系统动态事件触发下的系统状态变化、触发时刻、动态变量变化

Fig. 2 State evolution, triggering instants, and changes of the dynamic variables under dynamic event-triggered mechanism

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图 3 多智能体系统动态事件触发机制下的误差变化

Fig. 3 Error change under dynamic event-triggered mechanism

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图 4 多智能体系统静态事件触发下的系统状态变化和触发时刻

Fig. 4 State evolution and triggering instants under static event-triggered mechanism

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图 5 不同参数下系统中各智能体误差的平方和

Fig. 5 Sum of squares of the errors under different parameters

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图 6 不同参数下多智能体系统触发次数的变化

Fig. 6 Numbers of triggering instants under different parameters

下载: 全尺寸图片幻灯片

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