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

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.