• Dec 31, 2019 News!Welcome Assoc. Prof. David E. Breen from USA to join the Editorial board of IJMO.   [Click]
  • May 15, 2019 News!Vol.7, No.5- Vol.8, No.4 have been indexed by EI (Inspec).   [Click]
  • Apr 10, 2020 News!Vol. 10, No. 3 has been published with online version.   [Click]
General Information
    • ISSN: 2010-3697  (Online)
    • Abbreviated Title: Int. J. Model. Optim.
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET), EBSCO, etc.
    • E-mail ijmo@iacsitp.com
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2011 Vol.1(4): 296-301 ISSN: 2010-3697
DOI: 10.7763/IJMO.2011.V1.51

Design, Simulation and Implementation of a Full Bridge Series-Parallel Resonant DC-DC Converter using ANN Controller

Mohammad Jafari and Zahra Malekjamshidi

Abstract—A new method of control for high-voltage Full Bridge Series-Parallel Resonant (FBSPR) DC-DC converter with capacitive output filter, using Artificial Neural Networks (ANN) is proposed in this paper. The output voltage regulation obtained via high switching frequency and Soft switching operation (ZCS and ZVS technologies) to decrease the losses and optimize the efficiency of converter. In the following sections, a Small-Signal Model of FBSPR converter on base of first harmonic analysis and the generalized averaging method is derived. Then the obtained model is used to simulate the dynamic behavior of real converter using Matlab software. It was also used to obtain ideal control signals which are the desired ANN inputs and outputs and were saved as a training data set. The data set is then used to train the ANN to mimic the behavior of the ideal controller. In fact the ANN controller is trained according to the small signal model of converter and the ideal operating points. To compare the performances of simulated and practical ANN controller, a prototype is designed and implemented. The prototype is tested for step changes in both output load and reference voltage at steady state and under transient conditions. Comparison between experimental and simulations show a very good agreement and the reliability of ANN based controllers.

Index Terms—Full Bridge, Series-Parallel Resonant Converter, Artificial Neural Networks, ANN, ZVS, ZCS

The authors are with the Department of Electrical Engineering, Fasa branch, Islamic Azad University, Fasa, Iran. (E-mail: mohammad_jafari@iaufasa.ac.ir), (E-mail: zmalekjamshidi@miau.ac.ir).


Cite: Mohammad Jafari and Zahra Malekjamshidi, "Design, Simulation and Implementation of a Full Bridge Series-Parallel Resonant DC-DC Converter using ANN Controller," International Journal of Modeling and Optimization vol. 1, no. 4, pp. 296-301, 2011.

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