Abstract
The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks.We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot.A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks.
Highlights
Control over the safety factor profile and plasma pressure or stored energy is important for high performance tokamak operation, especially in hybrid and advanced scenarios [1]
Even if these actuator and plasma physics limits may not be restrictive at the target operating point, these are still limiting during transient phases
We presented in [10] a model predictive controller that uses multiple linearized models to control the q-profile while effectively dealing with constraints on actuators and physics limits in ITER simulations
Summary
Control over the safety factor profile and plasma pressure or stored energy is important for high performance tokamak operation, especially in hybrid and advanced scenarios [1]. The applied methods include adaptive control [2], backstepping control [3], passivity-based control [4, 5], Lyapunov control [6, 7], linear-quadratic-integral control [8, 9], model predictive control [10, 11] and robust control [12] Some of these have been implemented in experiments, others only in simulations. It is beneficial to prepare controllers well before being tested in experiments in order to minimize testing and commissioning time on the experiment This requires a controller development and test environment involving interfaces to plasma state reconstruction, a fast simulator and possibly experimental data. In this work we present a profile controller development and implementation software environment that is employed for pre-experiment simulations of four profile controllers as well as testing their performance in TCV experiments.
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