Active ramp-down control and trajectory design for tokamaks with neural differential equations and reinforcement learning

The tokamak offers a promising path to fusion energy, but disruptions pose a major economic risk, motivating solutions to manage their consequence. This work develops a reinforcement learning approach to this problem by training a policy to ramp-down the pl…