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Neural Computing and Applications

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19-03-2018 | Original Article

Analysis and design of single-phase power factor corrector with genetic algorithm and adaptive neuro-fuzzy-based sliding mode controller using DC–DC SEPIC

Authors: Subbiah Durgadevi, Mallapu Gopinath Umamaheswari

Published in: Neural Computing and Applications | Issue 10/2019

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Abstract

This paper proposes a methodology for single-phase power factor correction with DC–DC single-ended primary inductance converter (SEPIC) using cascade control strategy which comprises of genetic algorithm-based outer PI controller and an inner current controller which uses an adaptive neuro-fuzzy inference system-based sliding mode controller. DC–DC SEPIC is a fourth-order converter, and in order to reduce the complexity in controller design, reduced-order model of the original higher-order system is obtained by using Type-I Hankel matrix method. The performance of the proposed system is analysed using MATLAB/Simulink-based simulation studies. In order to ensure the robustness of the proposed controller, the performance parameters such as percentage total harmonic distortion, power factor, % voltage regulation, and % efficiency are analysed. From the simulation results, it is inferred that the proposed method provides efficient tracking of output voltage and effective source current shaping for load, line, and set point variations.

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Title: Analysis and design of single-phase power factor corrector with genetic algorithm and adaptive neuro-fuzzy-based sliding mode controller using DC–DC SEPIC
Authors: Subbiah Durgadevi
Mallapu Gopinath Umamaheswari
Publication date: 19-03-2018
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 10/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-018-3424-2

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