Integrated RMP-based ELM-crash-control process for plasma performance enhancement during ELM crash suppression in KSTAR

Abstract The integrated Resonant Magnetic Perturbation (RMP)-based Edge-Localized Mode (ELM)-crash-control process aims to enhance the plasma performance during RMP-driven ELM crash suppression, where RMP induces an unwanted confinement degradation. In this study, normalized beta ( β N ) is introduced as a metric for performance. incorporates latest achievements in technique efficiently. triggers n = 1 Edge-localized (ERMP) at L–H transition timing using real-time Machine Learning (ML) classifier. pre-emptive onset can reduce required external heating power achieving same by over 10% compared conventional onset. During phase, adaptive feedback controller, demonstrating its previous experiments, plays crucial role maximizing suppression phase and sustaining -enhanced state optimizing strength. achieves up ∼2.65 which ∼10% higher than KSTAR record but ∼6% lower target of K-DEMO first 2.8), maintains above limit (= 2.4) ∼4 s (∼60 $\tau_\textrm{E}$?> τ E ). addition enhancement, demonstrates quicker restoration recovery control with Conventional (CRMP). post-analysis experiment shows localized effect ERMP spectrum radial close relationship between evolution electron temperature.