Developments and Trends in Machine Learning for Electric Machine Drive Control and Monitoring

RAMESHWAR C. DOKHE , RAMDAS JARE , KOMAL DESAI

ML,AI,PS

Abstract— The literature on applying machine learning (ML) approaches to the control and monitoring of electric machine drives is methodically summarized in this review paper. The rapid advancement of specialized embedded hardware platforms and learning algorithms is expected to make machine learning (ML)-based data-driven approaches common tools for automated high-performance control and monitoring of electric drives. This article also offers some perspectives on how to encourage its broad implementation in the industry, with an emphasis on ML algorithm deployment on embedded system-on-chip field-programmable gate array devices.

Published Paper   E-Certificate

"Developments and Trends in Machine Learning for Electric Machine Drive Control and Monitoring", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.a572-a584, February-2024, Available :https://tijer.org/TIJER/papers/TIJER2402072.pdf

Volume 11 Issue 2, February-2024

Pages : a572-a584

Paper Reg. ID: TIJER_151240

Published Paper Id: TIJER2402072

Downloads: 000341

Research Area: Science and Technology

Country: PUNE, MAHARASHTRA , India

Published Paper PDF: https://tijer.org/TIJER/papers/TIJER2402072

Published Paper URL: https://tijer.org/TIJER/viewpaperforall?paper=TIJER2402072

ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: TIJER (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition