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  Published Paper Details:

  Paper Title

A Study On AI-Driven Machine Learning Approaches for Intelligent Control and Optimization in Power Electronics

  Authors

  Komala M H,  Smitha V Sajjan

  Keywords

Power Electronics, Artificial Intelligence (AI), Machine Learning (ML), Voltage Regulation, Power Converters, Computational Efficiency, Control Systems, Optimization, Adaptive Control, Smart Power Management, AI-Powered Switching, Medium-to-High Voltage Conditioning, AI Integration, Power Systems Engineering.

  Abstract


: This paper explores the integration of artificial intelligence (AI) technologies in power electronics applications, highlighting their role in enhancing voltage regulation and computational efficiency. As both fields continue to evolve, AI has emerged as a powerful tool for optimizing power electronics, particularly in converter control. Power electronics, a key domain in power systems engineering, focuses on medium-to-high voltage regulation, primarily through converters that require advanced control strategies for efficient power switching. AI's computational capabilities enable more precise and adaptive control, addressing the limitations of traditional methods. This study examines three major applications of AI in power electronics, discusses the challenges of implementation, and presents a roadmap for overcoming these obstacles. By bridging the gap between AI and power electronics, this research aims to pave the way for smarter, more efficient power management solutions

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2204741

  Paper ID - 279357

  Page Number(s) - g467-g471

  Pubished in - Volume 10 | Issue 4 | April 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Komala M H,  Smitha V Sajjan,   "A Study On AI-Driven Machine Learning Approaches for Intelligent Control and Optimization in Power Electronics", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 4, pp.g467-g471, April 2022, Available at :http://www.ijcrt.org/papers/IJCRT2204741.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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