基于观测的事件触发控制策略下随机多智能体系统一致性

王宏; 任志刚; 邢玛丽; 张波

doi:10.12052/gdutxb.240165

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基于观测的事件触发控制策略下随机多智能体系统一致性

控制科学与工程 | 更新时间：2026-05-27

- 基于观测的事件触发控制策略下随机多智能体系统一致性
- Consensus of Stochastic Multi-agent Systems via Observer-based Event-triggered Control Strategy
- 广东工业大学学报 2025年42卷第4期页码：96-104
- 作者机构：
  
  1. 广东工业大学自动化学院,广东,广州,510006
  2. 广东工业大学智能检测与制造物联教育部重点实验室,广东,广州,510006
  3. 广东工业大学粤港澳离散制造智能化联合实验室,广东,广州,510006
  4. 广东工业大学智能系统与优化集成广东省重点实验室,广东,广州,510006
- 作者简介：
  
  王宏(1998–) ，男，硕士研究生，主要研究方向为随机多智能体系统一致性问题、事件触发控制，E-mail：wanghong202324@163.com
  张波(1987–) ，男，副教授，硕士生导师，博士，主要研究方向为随机系统的稳定性和控制、混沌系统的同步、多智能体系统的共识以及复杂动态网络的同步，E-mail：zhangbo2018@gdut.edu.cn
- 基金信息：
  
  国家自然科学基金资助项目(62273101);广东省自然科学基金资助项目(2021A1515011343，2024A15155011768);浙江大学工业控制技术国家重点实验室开放研究项目(ICT2024B43);广州市科技计划项目(202201010251)
- DOI：10.12052/gdutxb.240165
  中图分类号： TP273
- 纸质出版：2025
- 稿件说明：
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王宏, 任志刚, 邢玛丽, 等. 基于观测的事件触发控制策略下随机多智能体系统一致性[J]. 广东工业大学学报, 2025, 42(4): 96–104.

Wang Hong, Ren Zhigang, Xing Mali, et al. Consensus of Stochastic Multi-agent Systems via Observer-based Event-triggered Control Strategy[J]. 2025, 42(4): 96-104.
王宏, 任志刚, 邢玛丽, 等. 基于观测的事件触发控制策略下随机多智能体系统一致性[J]. 广东工业大学学报, 2025, 42(4): 96–104. DOI： 10.12052/gdutxb.240165

Wang Hong, Ren Zhigang, Xing Mali, et al. Consensus of Stochastic Multi-agent Systems via Observer-based Event-triggered Control Strategy[J]. 2025, 42(4): 96-104. DOI： 10.12052/gdutxb.240165.

摘要

现实生活中物体的准确状态可能无法实时获得，利用观测值进行最优状态估计是有必要的。本文研究了基于观测的具有随机过程噪声和测量噪声的多智能体系统一致性。首先，根据卡尔曼滤波理论可以获得每个智能体的最优状态估计，并通过网络通信拓扑将该状态信息发送给相邻的智能体。然后，在相同的时间间隔内，为相邻节点定义一个新的事件触发测量误差函数，该函数能在该触发时刻获得相邻节点的非触发状态。此外，匹配相应的事件触发控制器，能有效地降低控制器更新频率，并得到多智能体系统均方一致性定理的判据。最后，通过数值仿真验证本文提出的事件触发控制协议的有效性。

Abstract

Due to the fact that the accurate state of object in real life may not be available in real-time

it is necessary to use observations for optimal state estimation. The consensus of Multi-Agent Systems (MASs) with stochastic process noise and measurement noise is investigated based on observations. Firstly

according to the theory of Kalman filtering

the optimal state estimation of each agent can be obtained and the state information is sent to adjacent agents through the network communication topology. Then

within the same time interval

a new event triggered measurement error function is defined for adjacent nodes

which can obtain the non-triggered state of adjacent nodes at that triggering moment. Additionally

a corresponding event-triggered controller is matched

effectively reducing the controller’s update frequency

and the criterion for the mean square consensus theorem of the MASs is obtained. Finally

the effectiveness of the proposed event triggered control protocol is verified through numerical simulation.

关键词

Keywords

references

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