基于混合双端事件触发机制的协同控制策略研究

李冬妮; 孙佳月; 闫宇晴; 张化光

doi:10.16383/j.aas.c240354

基于混合双端事件触发机制的协同控制策略研究

doi: 10.16383/j.aas.c240354 cstr: 32138.14.j.aas.c240354

李冬妮^{1, 2,},
孙佳月^{1, 2,},
闫宇晴^2,,
张化光^{1, 2,}

1.
东北大学流程工业综合自动化国家重点实验室沈阳 110819
2.
东北大学信息科学与工程学院沈阳 110819

基金项目: 中组部万人领军青年拔尖人才支持计划 (QNBJ-2023-12), 国家自然科学基金 (62203097), 中央高校基本科研业务专项资金 (N2404018) 资助

详细信息

作者简介:
李冬妮：东北大学信息科学与工程学院博士研究生. 2024年获得渤海大学硕士学位. 主要研究方向为自适应控制, 神经网络控制, 多智能体系统的分布式控制及其应用. E-mail: 2410269@stu.neu.edu.cn

孙佳月：东北大学信息科学与工程学院教授. 主要研究方向为复杂工业过程优化, 智能自适应学习, 多智能体系统分布式控制及其应用. 本文通信作者. E-mail: sunjiayue@ise.neu.edu.cn

闫宇晴：东北大学信息科学与工程学院博士研究生. 2018年获得辽宁师范大学学士学位. 主要研究方向为分数阶系统. E-mail: yanyuqing@whut.edu.cn

张化光：东北大学信息科学与工程学院教授. 主要研究方向为模糊控制, 随机系统控制, 基于神经网络控制, 非线性控制及其应用. E-mail: hgzhang@ieee.org

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出版历程
- 收稿日期: 2024-06-18
- 录用日期: 2024-11-06
- 网络出版日期: 2025-03-11
- 刊出日期: 2025-04-15

Cooperative Control Strategy Research Based on Hybrid Dual-terminal Event-triggered Mechanism

LI Dong-Ni^{1, 2
,},
SUN Jia-Yue^{1, 2
,},
YAN Yu-Qing^2
,,
ZHANG Hua-Guang^{1, 2
,}

1.
State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819
2.
College of Information Science and Engineering, Northeastern University, Shenyang 110819

Funds: Supported by National High-Level Talents Special Support Program (Youth Talent of Technological Innovation of Ten-Thousands Talents Program) (QNBJ-2023-12), National Natural Science Foundation of China (62203097), and the Fundamental Research Funds for the Central Universities (N2404018)

More Information

Author Bio:
LI Dong-Ni　Ph.D. candidate at the College of Information Science and Engineering, Northeastern University. She received her master degree from Bohai University in 2024. Her research interest covers adaptive control, neural-network control, and distributed control of multiagent systems and its applications

SUN Jia-Yue　Professor at the College of Information Science and Engineering, Northeastern University. Her research interest covers optimization of complex industrial processes, intelligent adaptive learning, and distributed control of multiagent systems and its applications. Corresponding author of this paper

YAN Yu-Qing　Ph.D. candidate at the College of Information Science and Engineering, Northeastern University. She received her bachelor degree from Liaoning Normal University in 2018. Her main research interest is fractional-order system

ZHANG Hua-Guang　Professor at the College of Information Science and Engineering, Northeastern University. His research interest covers fuzzy control, stochastic-system control, neural-network-based control, and nonlinear control and its applications

摘要

摘要: 针对非线性多智能体系统, 提出基于混合双端事件触发机制的模糊跟踪控制策略. 首先, 相比于现存状态触发机制, 构建一种灵活可调的阈值设计方法以满足系统实时性需求; 其次, 改进的状态触发机制将状态估计信号作为触发信号, 可有效降低现存机制的保守性并提高阈值设计的灵活性; 随后, 针对控制器−执行器环节和传感器−控制器环节, 设计混合双端事件触发机制来同时缓解双信道的通讯负担. 此外, 为解决未知不可测状态的问题, 构造一种仅基于相对输出信息的状态观测器. 最后, 在闭环系统内, 所有信号都是半全局一致最终有界稳定的, 并用一个实际的仿真例子证明了提出控制策略的可行性.
- 混合双端事件触发机制 /
- 改进的状态触发机制 /
- 多智能体系统 /
- 规定性能方法
Abstract: For nonlinear multiagent systems, this paper proposes the fuzzy tracking control strategy based on hybrid dual-terminal event-triggered mechanism. First of all, compared with existing state triggering mechanisms, a flexible and adjustable threshold designing method is constructed, which meets the real-time performance requirements of the system. Moreover, the improved state triggering mechanism considers the estimated state signal as the trigger signal, which effectively reduces the conservatism of existing mechanisms and enhances the flexibility of threshold design. Subsequently, the hybrid dual-terminal event-triggered mechanism is designed for controller to actuator link and sensor to controller link, which releases dual channel communication pressure, simultaneously. Besides, to solve the problem of unknown unmeasurable state, the state observer is constructed, which bases solely on relative output information. Finally, all the signals are semiglobally uniformly ultimately bounded in the closed-loop system, and a practical simulation example demonstrates the feasibility of the proposed control strategy.
- Hybrid dual-terminal event-triggered mechanism /
- improved state triggering mechanism /
- multiagent systems /
- prescribed performance method

HTML全文

图 1 通讯拓扑图

Fig. 1 The communication topology graphs

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图 2 4个跟随者和1个领导者的输出轨迹

Fig. 2 The output trajectories of the four followers and one leader

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图 3 跟踪误差的轨迹

Fig. 3 The trajectories of tracking errors

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图 4 控制器的输入轨迹

Fig. 4 The input trajectories of the controllers

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图 5 自适应律参数$\hat{\eta}_{h,\;1}$的轨迹

Fig. 5 The trajectories of the adaptive law parameters $\hat{\eta}_{h,\;1}$

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图 6 自适应律参数$\hat{\eta}_{h,\;2}$的轨迹

Fig. 6 The trajectories of the adaptive law parameters $\hat{\eta}_{h,\;2}$

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图 7 观测误差$\Delta_{h,\;2} $的变化情况

Fig. 7 The changes in observation errors $\Delta_{h,\;2}$

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图 8 4个智能体的事件触发间隔时间

Fig. 8 The event triggering interval time of four agents

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