Speaker
Jaemin Seo
(Chung-Ang University)
Description
The tokamak is one of the most promising concepts for confining fusion plasma. Controlling the tokamak actuators to stably maintain plasma in the desired state is an essential technology for sustainable energy production using nuclear fusion. Recently, technologies controlling fusion plasma in the tokamak using deep reinforcement learning (RL) have been emerging. In this presentation, we will present research results on optimizing the actuation trajectory, controlling the plasma state, and maintaining the plasma stability in tokamak devices using deep RL.
| Primary Keyword | AI-based controls |
|---|---|
| Secondary Keyword | ML-based optimization |
| Tertiary Keyword | reinforcement learning |
Primary author
Jaemin Seo
(Chung-Ang University)
