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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Veröffentlicht in:Proceedings of the IEEE International Symposium on Industrial Electronics (Online) S. 224 - 229
Hauptverfasser: Saeed, Junaid, Wang, Liuping
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.06.2018
Schlagworte:
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
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Abstract 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.
AbstractList 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.
Author Saeed, Junaid
Wang, Liuping
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  organization: Royal Melbourne Institute of Technology (RMIT), Melbourne, 3000, Victoria
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  givenname: Liuping
  surname: Wang
  fullname: Wang, Liuping
  organization: Royal Melbourne Institute of Technology (RMIT), Melbourne, 3000, Victoria
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Snippet The computational burden of an optimization problem plays an important role in real-time implementation of model predictive control (MPC) on fast sampling...
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SubjectTerms constraint
Control design
dc-dc
DC-DC power converters
full-bridge
Inductors
Laguerre functions
model predictive control
Predictive control
Switches
Switching frequency
Title Efficient Model Predictive Control of Full-Bridge DC-DC Converter Using Laguerre Functions
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