Abstract: In the context of Industry 4.0, traditional industrial control system architectures are undergoing structural transformations. The industry envisions leveraging 5G technology to reshape industrial control networks and to build a new generation of more flexible and open cloud–edge–device industrial control architectures. In this emerging architecture, industrial controllers are migrated from the field to the cloud, enabling large-scale collaborative control of field devices via 5G networks. However, in current industrial control systems, the connection between controllers, actuators, and sensors relies heavily on industrial ethernet protocols. For motion control tasks, in particular, the synchronization mechanism provided by the EtherCAT protocol is essential to enable precise and synchronized multi-axis motion. Therefore, to apply 5G in core industrial production processes, it is necessary to explore compatibility solutions between 5G and industrial ethernet protocols such as EtherCAT, as well as to evaluate the capability of 5G networks to support motion control tasks. In this study, an EtherCAT motion control system integrating 5G and cloud-based PLC is designed. To address the technical challenges inherent in such a system, the following solutions are proposed: (1) To solve the compatibility issue between 5G and EtherCAT industrial Ethernet protocols, a VXLAN-based integrated networking scheme is introduced. This scheme utilizes network virtualization to construct a Layer 2 virtual tunnel over the 5G network, enabling the transmission of EtherCAT data frames over 5G. (2) In view of the performance differences between 5G and industrial ethernet, this study conducts a quantitative analysis of the impact of network delay jitter on motion control stability. A mathematical model is established between system delay jitter and the stable control cycle, providing theoretical guidance for using 5G in motion control applications. Based on the above technical solutions, a 5G–EtherCAT integrated motion control test platform is developed. The PLC and EtherCAT master are deployed within the 5G core network, and servo motor control is realized via the 5G network. Finally, motion control performance tests are conducted under various control cycles in both the 5G–EtherCAT integrated network scenario and a wired network scenario. The experimental results verify the correctness of the theoretical model and demonstrate that 5G network (Release 15) can support low-precision motion control applications with a 25ms control cycle.