With the advent of 5G era, factories are transitioning towards wireless networks to break free from the limitations of wired networks. In 5G-enabled factories, unmanned automatic devices such as automated guided vehicles and robotic arms complete production tasks cooperatively through the periodic control loops. In such loops, the sensing data is generated by sensors, and transmitted to the control center through uplink wireless communications. The corresponding control commands are generated and sent back to the devices through downlink wireless communications. Since wireless communications, sensing and control are tightly coupled, there are big challenges on the modeling and design of such closed-loop systems. In particular, existing theoretical tools of these functionalities have different modelings and underlying assumptions, which make it difficult for them to collaborate with each other. Therefore, in this paper, an analytical closed-loop model is proposed, where the performances and resources of communication, sensing and control are deeply related. To achieve the optimal control performance, a co-design of communication resource allocation and control method is proposed, inspired by the model predictive control algorithm. Numerical results are provided to demonstrate the relationships between the resources and control performances.

翻译：随着5G时代的到来，工厂正朝着无线网络转型，以摆脱有线网络的束缚。在5G赋能的工厂中，自动导引车和机械臂等无人自动化设备通过周期性控制环路协同完成生产任务。在此类环路中，传感器生成感知数据，并通过上行无线通信传输至控制中心；相应的控制指令生成后，通过下行无线通信回传至设备。由于无线通信、感知与控制三者紧密耦合，此类闭环系统的建模与设计面临重大挑战。尤其值得注意的是，现有面向这些功能的理论工具具有不同的建模方式和底层假设，导致它们难以相互协作。因此，本文提出了一种解析闭环模型，其中通信、感知与控制的性能及资源深度关联。为实现最优控制性能，受模型预测控制算法启发，提出了一种通信资源分配与控制方法的协同设计方案。数值结果展示了资源与控制性能之间的关联关系。