Efficient Model Predictive Control of Full-Bridge DC-DC Converter using Laguerre Functions

The computational burden of an optimization problem plays an important role in real-time implementation of model predictive control (MPC) on fast sampling power electronic converters. This paper presents a computationally efficient Laguerre functions based constrained model predictive control (MPC) approach for a phase-shift full-bridge (PSFB) dc-dc converter. The subject plant is a single-input, single-output (SISO) system for which the control objective is to regulate the output voltage at a reference while respecting a nonlinear constraint on peak inductor current. It has been shown that by carefully tuning the Laguerre parameters, a closed loop performance equivalent to a long horizon MPC can be achieved with significantly lower computational burden, hence facilitating the converter operation at a high switching frequency. The performance of the designed controller has been verified on virtual hardware built in MATLAB/Simulink operating at a switching frequency of 25kHz.