A Kalman filter for feedback control of rotating external kink instabilities in the presence of noise

Jeremy M. Hanson, Bryan De Bono, Jeffrey P. Levesque, Michael E. Mauel, David A. Maurer, Gerald A. Navratil, Thomas Sunn Pedersen, Daisuke Shiraki, Royce W. James

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

The simulation and experimental optimization of a Kalman filter feedback control algorithm for n=1 tokamak external kink modes are reported. In order to achieve the highest plasma pressure limits in ITER, resistive wall mode stabilization is required [T. C. Hender, Nucl. Fusion 47, S128 (2007)] and feedback algorithms will need to distinguish the mode from noise due to other magnetohydrodynamic activity. The Kalman filter contains an internal model that captures the dynamics of a rotating, growing n=1 mode. This model is actively compared with real-time measurements to produce an optimal estimate for the mode's amplitude and phase. On the High Beta Tokamak-Extended Pulse experiment [T. H. Ivers, Phys. Plasmas 3, 1926 (1996)], the Kalman filter algorithm is implemented using a set of digital, field-programmable gate array controllers with 10 μs latencies. Signals from an array of 20 poloidal sensor coils are used to measure the n=1 mode, and the feedback control is applied using 40 poloidally and toroidally localized control coils. The feedback system with the Kalman filter is able to suppress the external kink mode over a broad range of phase angles between the sensed mode and applied control field. Scans of filter parameters show good agreement between simulation and experiment, and feedback suppression and excitation of the kink mode are enhanced in experiments when a filter made using optimal parameters from the scans is used.

Original languageEnglish
Article number056112
JournalPhysics of Plasmas
Volume16
Issue number5
DOIs
StatePublished - 2009
Externally publishedYes

Funding

The authors gratefully acknowledge the technical support of J. Andrello and N. Rivera during the course of this work. This work was supported by the U.S. Department of Energy Grant No. DE-FG02-86ER53222.

FundersFunder number
U.S. Department of Energy

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