电子科技2026，Vol.39Issue(1)：32-39,8.DOI:10.16180/j.cnki.issn1007-7820.2026.01.005
事件触发机制下网络化系统的模型预测控制研究综述
A Review of Research on Model Predictive Control for Networked Control Systems with Event-Triggered Mechanisms
摘要
Abstract
The design of networked systems integrates relevant technical solutions from fields such as control sys-tems,communication,and real-time computing.Due to the influence of the physical environment,both the communi-cation bandwidth and computing resources in networked control systems are limited.The event-triggered control strategy can effectively address the issue of communication limitations.After adopting the event-triggered strategy,while changing the system model,it also affects the system performance.The model predictive control method can en-hance the robustness and security of the system.This study reviews the research progress on the modeling of event-trig-gered schemes in networked control systems and the co-design methods with controllers.It analyzes and introduces the mathematical models of triggering schemes such as dynamic event-triggered,switching-like event-triggered,ring e-vent-triggered,and stochastic event-triggered.It summarizes the practical applications of jointly designing controllers with event-triggered mechanisms in networked systems.Moreover,it proposes the existing problems and future research directions of model predictive control based on event-triggered in networked control systems.关键词
网络化控制系统/网络安全/事件触发采样与通信/动态事件触发/随机事件触发/环形事件触发/不确定性/模型预测控制Key words
networked control systems/network security/event-triggered sampling and communication/dynamic event triggering/stochastic event triggering/torus event triggering/uncertainty/model predictive control分类
信息技术与安全科学引用本文复制引用
黎黄菊,王建华,杜树新..事件触发机制下网络化系统的模型预测控制研究综述[J].电子科技,2026,39(1):32-39,8.基金项目
浙江省自然科学基金(LQ22F030011) （LQ22F030011）
湖州市自然科学基金(2022YZ35) （2022YZ35）
湖州市工业系统智能感知与优化控制重点实验室项目(2022-17)Natural Science Foundation of Zhejiang(LQ22F030011) （2022-17）
Natural Science Foundation of Huzhou(2022YZ35) （2022YZ35）
Project of Huzhou Key Labora-tory of Intelligent Sensing and Optimal Control of Industrial Systems(2022-17) （2022-17）
