Current Profile Evolution Modeling via Subspace Identification Algorithms
C. Xu, Y. Ou, E. Schuster, J. Ferron, T.C. Luce, M.L. Walker, D.A. Humphreys, T.A. Casper, W.H. Meyer
Division of Plasma Physics (DPP) Annual Meeting of the American Physical Society (APS)
Dallas, Texas, November 17-21, 2008
Abstract
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Feedback control in advanced tokamaks requires suitable mathematical
models. First-principle modeling is sometimes limited by the lack of
theoretical or experimental knowledge of some of the plasma properties.
System identification arises as an alternative approach to
first-principle modeling, and deals with the problem of generating
dynamic models from measured input-output experimental data. We report
progress on two identification problems; a bilinear identification
(BiLinID) problem for the current ramp-up phase, and a linear
identification (LinID) problem for the current flattop phase. Subspace
identification, a newly emerging branch in system identification, is
used in this work to generate databased models. The subspace
identification method provides a state-space representation of the
system, enabbling computational simplicity and effectiveness for
multivariable systems.