Digital Twin-Based Autonomous Plasma Stabilization and Computational Resource Integration in Fusion Reactors

This paper proposes a next-generation control paradigm for nuclear fusion reactors based on an autonomous predictive system integrated with a high-fidelity digital twin. Unlike conventional reactive feedback control, which is constrained by time delays and cannot suppress fast non-linear disruptions, the proposed approach predicts plasma behavior in advance using physics-based models and deep learning. By proactively guiding plasma toward stable attractors or exploiting its non-linear dynamics for information processing, the system enables continuous stable operation, drastically reduces control energy, and introduces the concept of plasma computing within fusion reactors.