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Procedia Computer Science
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Procedia Computer Science
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Procedia Computer Science
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Performance Comparison of SVPWM and ANN based SVPWM Technique for Power Quality Improvement

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2016 English Publisher:Elsevier BVJournal:Procedia Computer Science, volume 93, pages 1,024-1,037 (issn: 1877-0509, Copyright policy )
Authors: Kumar, Rajiv; Singh, S.P.; Kumar, Bhavnesh;

doi: 10.1016/j.procs.2016.07.306

Performance Comparison of SVPWM and ANN based SVPWM Technique for Power Quality Improvement

Abstract

AbstractIn this paper a modulator based on ANN for power quality improvement is presented. A low computational intensive ANN based SVPWM is designed for controlling a three-phase neutral clamped bidirectional three level rectifier. The performance of the system with SPWM and SVPWM technique is investigated and compared under different operating conditions through a developed simulation model in MATLAB/Simulink environment.

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Keywords

multilevel converters, Artificial Neural Network (ANN), Modulation Techniques

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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