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)...

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Bibliographic Details
Published in:Proceedings of the IEEE International Symposium on Industrial Electronics (Online) pp. 224 - 229
Main Authors: Saeed, Junaid, Wang, Liuping
Format: Conference Proceeding
Language:English
Published: IEEE 01.06.2018
Subjects:
constraint
Control design
dc-dc
DC-DC power converters
full-bridge
Inductors
Laguerre functions
model predictive control
Predictive control
Switches
Switching frequency
ISSN:2163-5145
Online Access:Get full text
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Summary: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.
ISSN:2163-5145
DOI:10.1109/ISIE.2018.8433662