Finite-word-length FPGA implementation of model predictive control for ITER resistive wall mode control

TL;DR

This paper presents a finite-word-length FPGA implementation of model predictive control for stabilizing resistive wall modes in tokamaks, aiming to enable real-time control with reduced computational resources.

Contribution

It introduces a FPGA-based FWL implementation of MPC for RWM control, enhancing speed and efficiency over traditional PC methods.

Findings

FPGA implementation achieves faster computation times.

Comparable accuracy between FPGA and PC implementations.

Enables real-time control in tokamak experiments.

Abstract

In advanced tokamak scenarios, active feedback control of unstable resistive wall modes (RWM) may be required. A RWM is an instability due to plasma kink at higher plasma pressure, moderated by the presence of a resistive wall surrounding the plasma. We address the dominant kink instability associated with the main nonaxisymmetric (n = 1) RWM, described by the CarMa model. Model predictive control (MPC) is used, with the aim of enlarging the domain of attraction of the unstable RWM modes subject to power-supply voltage constraints. The implementation of MPC is challenging, because the related quadratic programming (QP) on-line optimization problems must be solved at a sub-ms sampling rate. Using complexity-reduction pre-processing techniques and a primal fast gradient method (FGM) QP solver, sufficiently short computation times for ITER are reachable using a standard personal computer (PC). In this work we explore even faster finite-word-length (FWL) implementation using field-programmable gate arrays (FPGA), which would facilitate experimental testing of such control algorithms on dynamically faster medium-sized tokamaks, and compare the computational accuracy and time with the PC implementation.