An Anti-Latency Intelligent Control for 5G Wireless Networks Based on End-Edge-Cloud Collaboration

Le résumé fourni par la source

To address the challenge of implementing 5G wireless networks in industrial process control, this paper integrates deep learning and reinforcement learning in AI with anti-disturbance industrial control to propose an anti-latency optimized control method for 5G wireless networks. The proposed method includes: an anti-latency controller based on data-driven signal compensators with PID controllers and the controller parameters self-optimization algorithm combining digital twin and reinforcement learning. The proposed anti-latency control method is integrated with end-edge-cloud collaboration technologies of Industrial Internet to create an intelligent control system architecture that achieves anti-latency optimized control. A control experimental system based on commercial 5G and Industrial Ethernet was established, and anti-latency control experiments are conducted on an actual heat exchange system. The experimental results indicate that the proposed anti-latency intelligent control method significantly eliminates the impact of 5G random latency on the dynamic performance of the control system.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.