Dynamic Operation of Buck-Boost DC-DC Converters over Wide Operating Ranges with Switching Based Model Predictive Control (MPC)

Abstract

In this paper, a novel model predictive control (MPC) scheme is proposed for buck-boost converters for achieving a high control bandwidth over wide operating ranges. There, the duty cycles of the four possible switching states are considered as control inputs, such that an exact state propagation can be accurately predicted in a large-signal linear model. Unlike conventional methods, which suffer from poor dynamic control performance when the input voltage is close to the output voltage, the proposed method achieves good dynamic and steady-state control performance independent of the operating point by actively utilizing all four switches during transients and switching only two switches during the steady-state. The resulting quadratic programming (QP) problem enables a real-time implementation of the proposed MPC method at a fast sampling rate.