3 papers
physics.plasm-ph2025
Plasma Shape Control via Zero-shot Generative Reinforcement Learning
Niannian Wu, Rongpeng Li, Zongyu Yang +6
Traditional PID controllers have limited adaptability for plasma shape control, and task-specific reinforcement learning (RL) methods suffer from limited generalization and the nee…
physics.plasm-ph2025
FusionMAE: large-scale pretrained model to optimize and simplify diagnostic and control of fusion plasma
Zongyu Yang, Zhenghao Yang, Wenjing Tian +14
In magnetically confined fusion device, the complex, multiscale, and nonlinear dynamics of plasmas necessitate the integration of extensive diagnostic systems to effectively monito…
physics.plasm-ph2025
High-Fidelity Data-Driven Dynamics Model for Reinforcement Learning-based Control in HL-3 Tokamak
Niannian Wu, Zongyu Yang, Rongpeng Li +11
The success of reinforcement learning (RL)-based control in tokamaks, an emerging technique for controlled nuclear fusion with improved flexibility, typically requires substantial…