Industrial Metaverse-Powered Interactive and Self-Healing Control Method for Combustion System

Abstract

To improve the active immunity and robustness of the combustion system of the thermal power unit following network attacks on industrial cyber-physical system controllers, this study applies the advanced possibilities of the industrial metaverse to industrial intelligent control and proposes a conceptual model architecture of industrial metaverse powered interactive and self-healing control (I-Metaverse-C) method. It has three technical features: namely, pluralistic coexistence, intelligent control, and value interoperability, to design a self-healing controller and an imitation expert operating experience model based on industrial digital twin under I-Metaverse-C. First, based on Newton's law of motion, the I/O data of the combustion system are extracted to establish the motion model of pluralistic control process coexistence in the I-Metaverse-C system. Second, a self-healing control system is established based on digital twin technology under the model architecture of I-Metaverse-C, and key physical process variables are determined to design the velocity and acceleration self-healing factors. Third, the imitation expert operating experience model of autonomous learning expert operating experience in value interoperability and seamless human-in-the-loop interaction is developed. Finally, theoretical proof and experiments comparing the combustion system after a network attack are conducted. The experimental findings indicate that the I-Metaverse-C improves the safety, stability, rapidity, and accuracy of the adjustment process of the combustion system during it is attacked by a network and that the imitation-expert operating experience model endows I-Metaverse-C with the capability to learn from expert experience.