{"title":"间歇观测的多控制器联网控制系统的帕累托最优控制","authors":"Cheng Tan;Qinglong Zhang;Jianying Di;Yuzhe Li","doi":"10.1109/LCSYS.2024.3489394","DOIUrl":null,"url":null,"abstract":"This letter explores Pareto optimal control for networked control systems (NCSs) featuring multiple controllers and an estimator under Denial-of-Service (DoS) attacks. First, we address the intermittent observation issues due to DoS attacks by employing an optimal state estimator. We then introduce a novel Pareto optimal strategy for NCSs under consideration, grounded in generalized difference Riccati equations (GDREs), to optimize joint control among multiple controllers and minimize the weighted sum cost function. Finally, we apply our strategies to computation offloading in mobile edge computing networks (MECNs), demonstrating the practicality and effectiveness of the proposed approach.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"2457-2462"},"PeriodicalIF":2.4000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pareto Optimal Control for Multi-Controller Networked Control Systems With Intermittent Observation\",\"authors\":\"Cheng Tan;Qinglong Zhang;Jianying Di;Yuzhe Li\",\"doi\":\"10.1109/LCSYS.2024.3489394\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This letter explores Pareto optimal control for networked control systems (NCSs) featuring multiple controllers and an estimator under Denial-of-Service (DoS) attacks. First, we address the intermittent observation issues due to DoS attacks by employing an optimal state estimator. We then introduce a novel Pareto optimal strategy for NCSs under consideration, grounded in generalized difference Riccati equations (GDREs), to optimize joint control among multiple controllers and minimize the weighted sum cost function. Finally, we apply our strategies to computation offloading in mobile edge computing networks (MECNs), demonstrating the practicality and effectiveness of the proposed approach.\",\"PeriodicalId\":37235,\"journal\":{\"name\":\"IEEE Control Systems Letters\",\"volume\":\"8 \",\"pages\":\"2457-2462\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Control Systems Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10740004/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Control Systems Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10740004/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
摘要
这篇文章探讨了在拒绝服务（DoS）攻击下，具有多个控制器和一个估计器的网络控制系统（NCS）的帕累托最优控制。首先，我们通过使用最优状态估计器来解决 DoS 攻击导致的间歇性观测问题。然后，我们在广义差分里卡蒂方程（GDRE）的基础上，为所考虑的 NCS 引入了一种新的帕累托最优策略，以优化多个控制器之间的联合控制，并使加权和成本函数最小化。最后，我们将策略应用于移动边缘计算网络（MECN）的计算卸载，证明了所提方法的实用性和有效性。
Pareto Optimal Control for Multi-Controller Networked Control Systems With Intermittent Observation
This letter explores Pareto optimal control for networked control systems (NCSs) featuring multiple controllers and an estimator under Denial-of-Service (DoS) attacks. First, we address the intermittent observation issues due to DoS attacks by employing an optimal state estimator. We then introduce a novel Pareto optimal strategy for NCSs under consideration, grounded in generalized difference Riccati equations (GDREs), to optimize joint control among multiple controllers and minimize the weighted sum cost function. Finally, we apply our strategies to computation offloading in mobile edge computing networks (MECNs), demonstrating the practicality and effectiveness of the proposed approach.
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