Machine Learning based Voltage Regulation Technique using Smart Rotating Magnetic Inverter

Muhammad Hussain*, Muhammad Siddique, Waqas Javed, Abdul Razaq, Muhammad Naveed Akhter, Farhan Hameed Malik

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


In this paper, a control methodology for power distribution line voltage regulations is presented. The salient features of this rotating magnetic inverter (RMI) include novel architecture with reduced electronic components and simple circuitry rather than conventional inverters, making it very economical and easy to implement. A new adaptive control based on a fuzzy logic approach is discussed in this paper, enabling the inverter to work more efficiently for dynamic voltage regulation. This proposed control method is best to mitigate the effect of voltage sags and swells in power distribution lines. On dynamic load variations, the system becomes unstable, and output contains voltage harmonics. Moreover, the RMI is a novel contribution from the authors as it has a unique structure for rotation of magnetic fields. The claim about the performance of the proposed RMI is tested and verified through MATLAB simulation.
Original languageEnglish
Title of host publication2022 International Conference on Electrical, Computer, and Energy Technologies (ICECET)
ISBN (Electronic)9781665470872
Publication statusPublished - 9 Sept 2022


  • RM inverter
  • fuzzy logic control
  • voltage regulation
  • voltage sag and swells

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Media Technology
  • Instrumentation


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