Tracking of Current and Rotation Profile Evolution in the DIII-D Tokamak via System Identification

W. Wehner, E. Schuster, M. L. Walker, D. A. Humphreys, Y. In

Division of Plasma Physics (DPP) Annual Meeting of the American Physical Society (APS)

Chicago, Illinois, November 8-12, 2010

Abstract

Transport theories produce nonlinear models based on partial differential equations (PDEs) whose complexity often renders them difficult to use for control design. As an alternative, data-driven modeling techniques involving system identification have the potential to obtain practical, low-complexity, dynamic models for the control of plasma systems. The plasma dynamics is first assumed to be governed by a tractable model with unknown and to-be-estimated transport coefficients. After discretizing both in space and time, the system states and to-be- estimated coefficients are combined into an augmented state vector. The resulting nonlinear state-space model is used for the design of an extended Kalman filter that provides real-time estimates not only of the system states but also of the unknown transport coefficients required by the current and rotation feedback controllers.