Density control in ITER: an iterative learning control and robust control approach

• DOI: 10.1088/1741-4326/aa95ce
• Publication Date: 2017-10-25T10:15:19Z
• Authors: T. Ravensbergen; P.C. de Vries; F. Felici; T.C. Blanken; R. Nouailletas; L. Zabeo
• Keywords: Feed forward; Iterative Learning Control; Tracking (education); Plasma actuator

Plasma density control for next generation tokamaks, such as ITER, is challenging because of multiple reasons. The response the usual gas valve actuators in future, larger fusion devices, might be too slow feedback control. Both pellet fuelling and use feedforward-based may help to solve this problem. Also, tight limits arise during ramp-up, due operational related divertor detachment radiative collapses. As number shots available controller tuning will limited paper, iterative learning (ILC) proposed determine optimal feedforward actuator inputs based on tracking errors, obtained previous shots. This method can take into account deal with large delays. However, a purely not sufficient presence disturbances shot-to-shot differences. Therefore, robust synthesis used construct robustly stabilizing controller. In simulations, it shown that combined strategy able achieve good performance differences, constraints, model mismatches.