The authors report on the implementation of a data-efficient machine learning approach to predict plasma dynamics. This enables offline design of robust trajectories to terminate the plasma without disruptive instabilities. Experimental results at the TCV tokamak show statistically significant improvements in key figures of merit and the ability to a priori predict the dynamics of key plasma properties.
- Allen M. Wang
- Alessandro Pau
- Stefano Marchioni
