Sensing data and control commands are frequently exchanged over communication networks for remote data acquisition and distributed control in industrial network control systems. The system performance relies on the design of sensing, transmission, and control. Due to the harsh environment in industrial field and the limited network resources, it is very challenging to meet the high requirement on transmission reliability for remote feedback control. In order to enhance the transmission ability for this kind of systems, an edge-assisted system architecture is proposed for the sensing and control processes. The parameter estimation for the sensing process is executed in the so-called edge estimator, and the controller is designed in a remote control center. Under this architecture, in this article an on-demand transmission scheme is designed by characterizing the overall effects of transmission reliability on the estimation and control performance. The overall system is optimized by formulating a revenue-cost maximization problem subject to the constraints of system stability, estimation convergence, spectrum utilization, and energy budget. The formulated mixed-integer nonlinear programming problem can be effectively solved with the block coordinate descent method. It is decomposed into two subproblems over disjoint variable sets. Simulation results demonstrate the advantages on both network-wide revenue and control-transmission cost.

中文翻译：

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工业网络系统中边缘辅助远程控制的按需传输


传感数据和控制命令经常通过通信网络进行交换，以实现工业网络控制系统中的远程数据采集和分布式控制。系统性能取决于传感、传输和控制的设计。由于工业现场环境恶劣，网络资源有限，满足远程反馈控制对传输可靠性的高要求非常具有挑战性。为了增强此类系统的传输能力，针对传感和控制过程提出了边缘辅助系统架构。传感过程的参数估计在所谓的边缘估计器中执行，控制器设计在远程控制中心中。在此架构下，本文通过表征传输可靠性对估计和控制性能的总体影响来设计按需传输方案。通过在系统稳定性、估计收敛性、频谱利用率和能量预算的约束下制定收入成本最大化问题来优化整个系统。所提出的混合整数非线性规划问题可以用块坐标下降法有效地求解。它被分解为两个不相交变量集的子问题。仿真结果证明了其在全网收入和控制传输成本方面的优势。