Robust Digital Control for an LLC Current-Resonant DC-DC Converter

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DOI: https://doi.org/10.37936/ecti-cit.201371.54355
Keywords:
LLC Current-Resonant DC-DC Converter Approximate 2DOF Digital Robust Control Micro-Processor

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Tomoya Nishimura
Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Japan
Yuto Adachi
Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Japan
Yoshihiro Ohta
Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Japan
Kohji Higuchi
Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Japan
Eiji Takegami
TDK-LAMBDA K.K., Japan
Satoshi Tomioka
TDK-LAMBDA K.K., Japan
Kamon Jirasereeamornkul
King Mongkut's University of Technology Thonburi, Thailand
Kosin Chamnongthai
King Mongkut's University of Technology Thonburi, Thailand

Abstract

If a pulse frequency and a load resistance of an LLC current-resonant DC-DC converter are changed, the dynamic characteristics are varied greatly, that is, the LLC current-resonant DC-DC converter has non-linear characteristics. In many applications of DC-DC converters, loads cannot be specified in advance, and they will be changed suddenly from no loads to full loads. A DC-DC converter system used a conventional single controller cannot be adapted to change dynamics and it occurs large output voltage variation. In this paper, a robust digital controller
for suppress the change of step response characteristics and variation of output voltage in the load sudden change is proposed. Experimental studies using a micro-processor for the controller demonstrate that this type of digital controller is effective to suppress the variation.

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How to Cite
[1]
T. Nishimura, “Robust Digital Control for an LLC Current-Resonant DC-DC Converter”, ECTI-CIT Transactions, vol. 7, no. 1, pp. 71–78, Apr. 2016.
Issue
Vol. 7 No. 1 (2013): ECTI Transaction on CIT (May 2013)
Section
Artificial Intelligence and Machine Learning (AI)