文献类型：期刊文献

英文题名：A Sensing-Network-Control Co-Design Framework for TSN-Enabled Industrial Cyber-Physical Systems

作者：Wang, Xiaolin[1,2];Wei, Yuhang[1];Li, Yao[3,4];Zhang, Jinglong[5];Guan, Xinping[5]

机构：[1]East China Univ Sci & Technol, Dept Math, Shanghai 200237, Peoples R China;[2]Minist Educ, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China;[3]Shanghai Univ, Sch Future Technol, Shanghai 200444, Peoples R China;[4]Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai, Peoples R China;[5]Shanghai Jiao Tong Univ, Sch Automation & Intelligent Sensing, Shanghai 200240, Peoples R China

年份：2026

卷号：4

起止页码：731

外文期刊名：IEEE TRANSACTIONS ON INDUSTRIAL CYBER-PHYSICAL SYSTEMS

收录：EI(收录号：20262721052274);Scopus(收录号：2-s2.0-105043724514);WOS:【ESCI(收录号:WOS:001843460700001)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 62303298, Grant 62303185, and Grant 62503326, in part by the Fundamental Research Funds for the Central Universities, and in part by the Explorers Program of Shanghai (Basic Research Funding) under Grant 25TS1402000.

语种：英文

外文关键词：Design methodology; Costing; Costs; Delays; Timing; Image sensors; Nickel; Schedules; Scheduling; Fluid flow; Industrial cyber-physical systems; co-design framework; TSN scheduling; H-2 optimal robust controller

摘要：In industrial cyber-physical systems, multiple control subsystems rely on large-scale sensors and industrial networks for collaborative closed-loop control. Although increasing the number of sensors can improve sensing quality and control accuracy, it also increases network load and changes network delay, which further affects closed-loop performance. Therefore, sensor deployment, network resource allocation, and controller design are tightly coupled across layers. To address this issue, this paper proposes a sensing-network-control co-design framework for multi-subsystem collaborative control. Leveraging the deterministic transmission capability of Time-Sensitive Networking (TSN), the proposed framework jointly models the relationships among the number of sensors, bandwidth allocation ratios, network delay, and control cost, and formulates a unified optimization problem integrating sensing, network, and control costs. Based on this framework, an optimal distributed H-2 controller with zero-order hold (ZOH) and a two-stage constraint-aware scheduling algorithm (TCSA) are developed to jointly optimize sensor deployment and network resource allocation. Simulation results validate the effectiveness of the proposed framework and the TCSA algorithm.