FPGA implementation of optimal and approximate model predictive control for a buck-boost DC-DC converter

Abstract

This paper proposes a method for FPGA implementation of explicit, piecewise affine (PWA) model predictive control (MPC) laws for non-inverting buck-boost DC-DC converters. A novel approach to obtain a PWA model of the power converter is proposed and two explicit MPC laws are derived, i.e., one based on the standard approach to synthesis of explicit MPC and one based on a simplicial PWA approximation of the resulting MPC law, which permits a more efficient implementation. An FPGA circuit is designed for both the original and the approximating MPC control law. Two hardware architectures with different FPGA footprint and computation latency are developed for each control law. Extensive real-time experiments demonstrate the performance of the two MPC controllers and their computational characteristics.