非线性连续系统动态量化器与小增益分布式模型预测控制的协同设计

IF 4 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

IEEE Transactions on Control of Network Systems Pub Date : 2025-01-07 DOI:10.1109/TCNS.2025.3526729

Yi Zheng;Yueyan Zhang;Shaoyuan Li;Min Luo

{"title":"非线性连续系统动态量化器与小增益分布式模型预测控制的协同设计","authors":"Yi Zheng;Yueyan Zhang;Shaoyuan Li;Min Luo","doi":"10.1109/TCNS.2025.3526729","DOIUrl":null,"url":null,"abstract":"This article presents a codesign control scheme that integrates distributed model predictive control with dynamic quantizers for networked nonlinear continuous systems operating under limited communication bandwidth. Each subsystem-based model predictive control formulation considers the dynamic quantizer's influence within the optimization problem in the proposed method. Both the quantizer parameters and the control law are optimized simultaneously in real time, which offers potential improvements in the performance of the closed-loop system within a certain communication limitation. A stability constraint based on small-gain Lyapunov theory is designed for each subsystem's controller, allowing for a relaxation of the restrictions on the closed-loop subsystems compared to decentralized approaches. In addition, a sufficient condition that ensures the stability of the overall system is provided. Simulation results demonstrate the effectiveness of the proposed codesign method.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1699-1708"},"PeriodicalIF":4.0000,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Codesign of Dynamic Quantizer and Small-Gain-Based Distributed Model Predictive Control of Nonlinear Continuous System\",\"authors\":\"Yi Zheng;Yueyan Zhang;Shaoyuan Li;Min Luo\",\"doi\":\"10.1109/TCNS.2025.3526729\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a codesign control scheme that integrates distributed model predictive control with dynamic quantizers for networked nonlinear continuous systems operating under limited communication bandwidth. Each subsystem-based model predictive control formulation considers the dynamic quantizer's influence within the optimization problem in the proposed method. Both the quantizer parameters and the control law are optimized simultaneously in real time, which offers potential improvements in the performance of the closed-loop system within a certain communication limitation. A stability constraint based on small-gain Lyapunov theory is designed for each subsystem's controller, allowing for a relaxation of the restrictions on the closed-loop subsystems compared to decentralized approaches. In addition, a sufficient condition that ensures the stability of the overall system is provided. Simulation results demonstrate the effectiveness of the proposed codesign method.\",\"PeriodicalId\":56023,\"journal\":{\"name\":\"IEEE Transactions on Control of Network Systems\",\"volume\":\"12 2\",\"pages\":\"1699-1708\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2025-01-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Control of Network Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10830009/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"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 Transactions on Control of Network Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10830009/","RegionNum":3,"RegionCategory":"计算机科学","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

针对通信带宽有限的网络非线性连续系统，提出了一种将分布式模型预测控制与动态量化相结合的协同设计控制方案。每个基于子系统的模型预测控制公式都考虑了动态量化器对优化问题的影响。同时对量化器参数和控制律进行实时优化，在一定的通信限制下提高了闭环系统的性能。为每个子系统的控制器设计了基于小增益Lyapunov理论的稳定性约束，与分散方法相比，允许放松对闭环子系统的限制。此外，还提供了保证整个系统稳定的充分条件。仿真结果验证了所提协同设计方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Codesign of Dynamic Quantizer and Small-Gain-Based Distributed Model Predictive Control of Nonlinear Continuous System

This article presents a codesign control scheme that integrates distributed model predictive control with dynamic quantizers for networked nonlinear continuous systems operating under limited communication bandwidth. Each subsystem-based model predictive control formulation considers the dynamic quantizer's influence within the optimization problem in the proposed method. Both the quantizer parameters and the control law are optimized simultaneously in real time, which offers potential improvements in the performance of the closed-loop system within a certain communication limitation. A stability constraint based on small-gain Lyapunov theory is designed for each subsystem's controller, allowing for a relaxation of the restrictions on the closed-loop subsystems compared to decentralized approaches. In addition, a sufficient condition that ensures the stability of the overall system is provided. Simulation results demonstrate the effectiveness of the proposed codesign method.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

IEEE Transactions on Control of Network Systems Mathematics-Control and Optimization

CiteScore

7.80

自引率

7.10%

发文量

169

期刊介绍： The IEEE Transactions on Control of Network Systems is committed to the timely publication of high-impact papers at the intersection of control systems and network science. In particular, the journal addresses research on the analysis, design and implementation of networked control systems, as well as control over networks. Relevant work includes the full spectrum from basic research on control systems to the design of engineering solutions for automatic control of, and over, networks. The topics covered by this journal include: Coordinated control and estimation over networks, Control and computation over sensor networks, Control under communication constraints, Control and performance analysis issues that arise in the dynamics of networks used in application areas such as communications, computers, transportation, manufacturing, Web ranking and aggregation, social networks, biology, power systems, economics, Synchronization of activities across a controlled network, Stability analysis of controlled networks, Analysis of networks as hybrid dynamical systems.