This paper presents the design and implementation of a distributed control system for the laser wakefield acceleration (LWFA) facility at Shanghai Institute of Optics and Fine Mechanics (SIOM), Chinese Academy of Sciences (CAS).This system is developed to support artificial intelligence (AI) integration and automated tuning.Built on the Experimental Physics and Industrial Control System (EPICS), it provides real-time monitoring, device control, alarm handling, and data archiving.To enhance modularity and scalability, unified multiuser interfaces were developed using Control System Studio (CSS) within a microservice architecture.Remote Direct Memory Access (RDMA) was adopted to remove bottlenecks in high-throughput image data transmission, and a hybrid storage framework combining MySQL, InfluxDB, and MinIO was implemented for efficient data storage and management.The system has been comprehensively tested in both laboratory and operational environments.This work offers a practical solution for the intelligent evolution of LWFA facilities, laying the groundwork for future AI-driven laser-plasma accelerator systems.
Li et al. (2026) studied this question.