Conveners
Data Analysis for Feedback Control
- Geert Verdoolaege (Ghent University)
Data Analysis for Feedback Control
- Geert Verdoolaege (Ghent University)
In magnetic confinement fusion, precise control of plasma dynamics and shape is essential for stable operation. We present two complementary developments toward real‑time, intelligent control on the HL‑3 tokamak. First, we build a high‑fidelity, fully data‑driven dynamics model to accelerate reinforcement learning (RL)–based trajectory control. By addressing compounding errors inherent to...
Impurity seeding plays a pivotal role in achieving plasma detachment by reducing heat and particle fluxes to divertor targets, yet requires precise real-time control of seeding rates. Current diagnostic limitations and manual adjustments impede this process. For instance, the credibility of Langmuir probes becomes suspect under the heating of reactor level [#1]. Additionally, line-integrated...
The complex multiscale nonlinear dynamics of magnetically confined plasmas necessitate integrating massive diagnostic systems with control actuators in tokamak reactors. The complexity brought by such massive systems and their tangled interrelations has been a main obstacle in the way of fusion power plant. In this work, a large-scale model, fusion masked auto-encoder (FusionMAE) is pretrained...
A real-time signal processing unit based on FPGA has been developed for electron temperature (Te) evaluation in a Thomson scattering (TS) diagnostic system. The FPGA module is independent of the polychromator and is integrated with ADC and DAC components as a compact real-time processing unit. It receives five analog input channels directly from the spectral outputs of the polychromator and...
A robust and interpretable neural network (NN)-based model has been developed for analyzing charge exchange spectra on the HL-2A tokamak, achieving high accuracy in ion temperature (T_i) and toroidal rotation velocity (v_t) estimation. Trained and tested on around 122 thousand spectra, the model achieves a coefficient of determination (𝑅²) of 0.948 for T_i and 0.973 for v_t, with an inference...
Accurate real-time control of plasma equilibrium is critical for stable tokamak operation. This study proposes a novel imitation learning framework to predict optimal feedforward currents for poloidal field (PF) coils based on plasma state observations. The model ingests high-dimensional state vectors including plasma boundary coordinates, plasma current centroid positions, and total plasma...
