非线性多智能体系统的动态事件触发固定时间一致性控制

邵蝉云; 安爱民; 徐承承; 刘向航; 李二超

doi:10.16383/j.aas.c250304

非线性多智能体系统的动态事件触发固定时间一致性控制

doi: 10.16383/j.aas.c250304 cstr: 32138.14.j.aas.c250304

1.
兰州理工大学自动化与电气工程学院兰州 730050

基金项目: 国家自然科学基金(61563032, 61963025, 62203196, 62463018), 甘肃省科技计划(22YF7GA164, 22CX8GA131, 22CX3GD005)资助

详细信息

作者简介:
邵蝉云：兰州理工大学自动化与电气工程学院硕士研究生. 主要研究方向为多智能体系统协同控制. E-mail: 14719449252@163.com

安爱民：兰州理工大学自动化与电气工程学院教授. 主要研究方向为复杂系统建模与智能协同优化控制技术, 机器人智能感知与控制理论及其应用, 多种可再生能源综合优化发电技术. 本文通信作者. E-mail: anaiminll@163.com

徐承承：兰州理工大学自动化与电气工程学院硕士研究生. 主要研究方向为高压设备绝缘监测. E-mail: 19909450235@163.com

刘向航：兰州理工大学自动化与电气工程学院硕士研究生. 主要研究方向为多智能体系统协同控制. E-mail: 18864966513@163.com

李二超：兰州理工大学自动化与电气工程学院教授. 主要研究方向为智能优化理论、方法及应用, 智能机器人环境感知、建模与控制, 综合能源系统建模与运行优化. E-mail: lecstarr@163.com

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出版历程
- 收稿日期: 2025-07-11
- 录用日期: 2025-10-27
- 网络出版日期: 2025-12-19

Dynamic Event-triggered Fixed-time Consensus Control for Nonlinear Multi-agent Systems

1.
College of Automation and Electrical Engineering, Lanzhou University of Technology, Lanzhou 730050

Funds: Supported by National Natural Science Foundation of China (61563032, 61963025, 62203196, 62463018) and Gansu Provincial Science and Technology Program (22YF7GA164, 22CX8GA131, 22CX3GD005)

More Information

Author Bio:
SHAO Chan-Yun　Master student at the College of Automation and Electrical Engineering, Lanzhou University of Technology. Her main research interest is cooperative control of multi-agent systems

AN Ai-Min　Professor at the College of Automation and Electrical Engineering, Lanzhou University of Technology. His research interests include complex system modeling and intelligent cooperative optimization control technology, intelligent perception and control theory of robots and their applications, and comprehensive optimization power generation technology of multiple renewable energy sources. Corresponding author of this paper

XU Cheng-Cheng　Master student at the College of Automation and Electrical Engineering, Lanzhou University of Technology. Her main research interest is insulation monitoring of high-voltage equipment

LIU Xiang-Hang　Master student at the College of Automation and Electrical Engineering, Lanzhou University of Technology. His main research interest is cooperative control of multi-agent systems

LI Er-Chao　Professor at the College of Automation and Electrical Engineering, Lanzhou University of Technology. His research interests include intelligent optimization theory, method and application, intelligent robot environment perception, modeling and control, and comprehensive energy system modeling and operation optimization

摘要

摘要: 研究通信拓扑固定下受有界扰动影响的非线性多智能体系统固定时间一致性问题. 针对现有事件触发控制方法存在的收敛时间依赖初值、扰动下触发可靠性低、控制参数缺乏理论设计依据等挑战, 提出一种动态事件触发固定时间一致性控制方法. 首先, 设计融合非线性增益与双曲正切扰动补偿的固定时间控制器, 在消除抖振的同时保证收敛时间上界严格独立于系统初始状态. 其次, 构造基于动态变量自适应调节的事件触发机制, 显著降低通信频率并严格证明系统不存在Zeno行为. 进一步, 通过建立新型Lyapunov稳定性分析框架, 显式给出收敛时间上界与事件触发间隔下界. 仿真结果表明, 所提方法在保证固定时间收敛性能的同时, 有效实现通信效率的优化提升.
- 多智能体系统 /
- 动态事件触发控制 /
- 固定时间一致性 /
- 非线性动力学 /
- 扰动抑制
Abstract: This paper investigates the fixed-time consensus problem for nonlinear multi-agent systems under bounded disturbances and a fixed communication topology. Addressing the challenges in existing event-triggered control methods, such as convergence time dependence on initial conditions, low triggering reliability under disturbances, and lack of theoretical basis for control parameter design, a dynamic event-triggered fixed-time consensus control method is proposed. Firstly, a fixed-time controller integrating nonlinear gain and disturbance compensation is designed, which uses hyperbolic tangent functions instead of sign functions to eliminate chattering and achieve smooth control signals, ensuring the upper bound of convergence time is strictly independent of initial states. Secondly, an event-triggered mechanism based on adaptive dynamic variables is constructed, significantly reducing communication frequency and rigorously excluding Zeno behavior. Furthermore, through the construction of a novel Lyapunov stability analysis framework, explicit expressions for the upper bound of convergence time and the lower bound of event-triggered interval are derived. Simulation results demonstrate that the proposed method ensures fixed-time convergence performance while effectively achieving optimization and improvement of communication efficiency.
- multi-agent systems /
- dynamic event-triggered control /
- fixed-time consensus /
- nonlinear dynamics /
- disturbance rejection

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图 1 通信拓扑图

Fig. 1 Communication topology diagram

下载: 全尺寸图片幻灯片

图 2 动态事件触发控制下多智能体系统状态同步对比

Fig. 2 Comparison of state synchronization in multi-agent systems under dynamic event-triggered control

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图 3 动态事件触发控制下多智能体系统通信触发间隔对比

Fig. 3 Comparison of communication triggering intervals of multi-agent systems under dynamic event-triggered control

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图 4 动态事件触发控制下多智能体系统输入轨迹对比

Fig. 4 Comparison of input trajectories of multi-agent systems under dynamic event-triggered control

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图 5 动态事件触发控制下测量误差与阈值演化对比

Fig. 5 Comparison of measurement error and threshold evolution under dynamic event-triggered control

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图 6 SETFC作用下各智能体的状态轨迹

Fig. 6 The state trajectory of each agent under SETFC

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图 7 SETFC作用下各智能体的控制输入

Fig. 7 The control input of each agent under SETFC

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图 8 SETFC作用下各智能体的触发时刻

Fig. 8 The triggering time of each agent under SETFC

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表 1 动态事件触发固定时间一致性算法主要参数

Table 1 Main parameters of dynamic event-triggered fixed-time consensus algorithm

参数	值
$ \lambda $	1.4
$ \overset\frown{u} $	3.0
$ \rho $	5.0
$ \sigma $	3.0
$ \varepsilon $	0.006
$ \delta $	0.4
$ K $	5.0
$ a $	2.0
$ b $	1.0
$ q $	1.4
$ p $	0.4

下载: 导出CSV

表 2 不同控制策略下智能体触发次数统计

Table 2 Triggering count statistic for agents under different control strategies

控制策略	跟随者1	跟随者2	跟随者3	跟随者4	总数
S-DETFC	231	529	509	496	1765
T-DETFC	63	74	67	57	261
SETFC	566	556	553	577	2252

下载: 导出CSV

表 3 不同控制策略下智能体触发间隔统计 (s)

Table 3 Triggering interval statistic for agents under different control strategies (s)

控制策略	跟随者1	跟随者2	跟随者3	跟随者4	均值
S-DETFC	0.0206	0.0168	0.0182	0.0198	0.0188
T-DETFC	0.0477	0.0525	0.0636	0.0641	0.0569
SETFC	0.0059	0.0050	0.0060	0.0049	0.0054

下载: 导出CSV

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