First experimental demonstration of plasma shape control in a tokamak through Model Predictive Control

TL;DR

This paper presents the first experimental implementation of plasma shape control in a tokamak using Model Predictive Control, combining plasma response models with real-time optimization to achieve desired plasma configurations.

Contribution

It introduces a novel MPC-based plasma shape control method tested experimentally on a tokamak, integrating linearized plasma models with magnetic control systems.

Findings

Successful experimental plasma shape regulation using MPC

Real-time quadratic programming implementation

Enhanced control precision demonstrated in tokamak experiments

Abstract

In this work, a Model Predictive Controller (MPC) is proposed to control the plasma shape in the Tokamak \`a Configuration Variable (TCV). The proposed controller relies on models obtained by coupling linearized plasma response models, derived from the \texttt{fge} code of the Matlab EQuilibrium toolbox (MEQ) suite, with a state-space description of the core TCV magnetic control system. It optimizes the reference signals fed to this inner control loop in order to achieve the desired plasma shape while also enforcing constraints on the plant outputs. To this end, a suitable Quadratic Programming (QP) problem is formulated and solved in real-time. The effectiveness of the proposed controller is illustrated through a combination of simulations and experimental results. To the best of our knowledge, this is the first time that a plasma shape control solution based on MPC has been experimentally tested on a real tokamak.