FPGA acceleration of Model Predictive Control for Iter Plasma current and shape control

TL;DR

This paper presents an FPGA-based implementation of a quadratic programming solver for Model Predictive Control in plasma shaping, achieving faster execution through high-level synthesis and parallelization techniques.

Contribution

It introduces a high-level synthesis approach to accelerate the dual Fast Gradient Method solver on FPGA for plasma control applications.

Findings

Achieved faster solver execution on FPGA

Parallelized matrix-vector operations within the iterative algorithm

Demonstrated suitability for real-time plasma control

Abstract

A faster implementation of the Quadratic Programming (QP) solver used in the Model Predictive Control scheme for Iter Plasma current and shape control was developed for Xilinx Field-Programmable Gate Array (FPGA) platforms using a high-level synthesis approach. The QP solver is based on the dual Fast Gradient Method (dFGM). The dFGM is essentially an iterative algorithm, where matrix-vector arithmetic operations within the main iteration loop may be parallelized. This type of parallelism is not well-suited to standard multi-core processors because the number of operations to be spread among processing threads is relatively small considering the time-scale of thread scheduling. The FPGA implementation avoids this issue, but it requires specific techniques of code optimization in order to achieve faster solver execution.