Robust Control of the Current Profile and Plasma Energy in EAST
H. Wang, E. Schuster
Fusion Engineering and Design, 146 (2019) 688–691.
Abstract
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Integrated control of the toroidal current density profile, or
alternatively the q-profile, and plasma stored energy is essential to
achieve advanced plasma scenarios characterized by high plasma
confinement, magnetohy- drodynamics stability, and noninductively
driven plasma current. The q-profile evolution is closely related to
the evolution of the poloidal magnetic flux profile, whose dynamics is
modeled by a nonlinear partial differential equation (PDE) referred to
as the magnetic-flux diffusion equation (MDE). The MDE prediction
depends heavily on the chosen models for the electron temperature,
plasma resistivity, and non-inductive current drives. To aid control
synthesis, control-oriented models for these plasma quantities are
necessary to make the problem tractable. However, a relatively large
deviation between the predictions by these control-oriented models and
experimental data is not uncommon. For this reason, the electron
temperature, plasma resistivity, and non- inductive current drives are
modeled for control synthesis in this work as the product of an "uncertain"
reference profile and a nonlinear function of the different auxiliary
heating and current-drive (H&CD) source powers and the total plasma
current. The uncertainties are quantified in such a way that the family
of models arising from the modeling process is able to capture the
q-profile and plasma stored energy dynamics from a typical EAST shot.
A control-oriented nonlinear PDE model is developed by combining the
MDE with the “uncertain” models for the electron temperature, plasma
resistivity, and non-inductive current drives. This model is then
rewritten into a control framework to design a controller that is robust
against the modeled uncertainties. The resulting controller utilizes
EAST's H&CD powers and total plasma current to regulate the q profile
and plasma stored energy even when mismatches between modeled and actual
dynamics are present. The effectiveness of the controller is demonstrated
through nonlinear simulations.