Model-based Static and Dynamic Filter Application to Resistive Wall Mode Identification and Feedback Control in DIII-D

A model-based algorithm has been developed and implemented in DIII-D to provide resistive wall mode (RWM) identification and feedback control. In particular, a dynamic Kalman filter has been installed to discriminate edge localized modes (ELMs) from RWM, in addition to a static matched filter. Recent experiments demonstrated that the Kalman filtering scheme was effective in discriminating ELM-noise from RWM. Whereas the state-space model for the Kalman filter used in the experiments was based on picture frame wall model, a more advanced model has been developed using wall surface current eigenmode approach. The wall eigenmode model-based algorithm is expected to be more effective in terms of ELM-discrimination, as well as prompt RWM response. The optimized Kalman estimates based on the developed state-space models will be combined with optimized state-feedback to build a model-based linear quadratic Gaussian (LQG) controller