Abstract:Highlights.• Algorithm vertical stabilisation using a linear parametrisation of the current density • Experimentally derived model of the vacuum vessel to account for vessel currents• Real-time contouring algorithm for flux surface averaged 1.5D transport equations• Full real time implementation coded in SIMULINK runs in less than 200µs• Applications: shape control, safety factor profile control, coupling with RAPTOR Abstract. Equilibrium reconstruction consists in identifying, from experimental measurements, … Show more
“…as well as the scalar Φ b (toroidal flux enclosed by plasma) can be timevarying and provided by a real-time (RT) equilibrium reconstruction codes such as LIUQE [21].…”
Section: • Geometry Profiles Quantitiesmentioning
confidence: 99%
“…While we expect the true q-profile to globally follow the trends reported here, we do not claim that the core q-profile estimate accurately represents the situation in the plasma. A comparison of the real-time reconstructed q-profiles used for control with reconstructed profiles from the equilibrium reconstruction code LIUQE [21] as well as interpretative ASTRA [35] simulations is given in section 8.…”
Section: Note On Current Density Profile Estimatesmentioning
confidence: 99%
“…Automatic detection and correction for diagnostic artefacts like fringe jumps in FIR channels is included. LIUQE A 2D Grad-Shafranov equilibrium reconstruction code that uses magnetic measurements [21]. It supplies equilibrium geometry information to the RAPTOR-observer, the RAPDENS-observer and the profile controller.…”
Section: Plasma State Reconstructionmentioning
confidence: 99%
“…the density, temperature and current distribution requires knowledge of these quantities in real-time. These quantities can be reconstructed using real-time equilibrium reconstruction [20,21] or dynamic state observers [22] that integrate the available (noisy) diagnostic signals into an estimate of the plasma state.…”
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.
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