Unit Prediction Horizon Binary Search-Based Model Predictive Control of Full-Bridge DC–DC Converter

Abstract

In this paper, we present a unit prediction horizon binary search-based nonlinear model predictive control (MPC) of phase shift full-bridge dc-dc converter, working in discontinuous conduction mode. The objective of the control algorithm is to regulate the output voltage of the converter to a reference set point while also respecting a nonlinear constraint on the peak inductor current. We utilize a large signal dynamic model of the converter based on the analytical solution of piecewise differential equations. The developed large signal model and the unit prediction horizon allow us to use a novel and computationally efficient approach based on the binary search algorithm to solve the optimization problem in the nonlinear MPC. The proposed algorithm offers faster optimization solution for MPC, thereby facilitating high frequency operation of the converter. We compare the computational complexity of the proposed algorithm with the integrated perturbation analysis and sequential quadratic programming algorithm. Furthermore, we address the problem of offset in the output voltage due to unmeasured load disturbances. We include experimental results illustrating the effectiveness of the proposed control scheme on a 500-W converter setup operating on a switching frequency of 20 kHz.