Fulltext

Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement

Hannan MA 1 , Ali JA 2 , Hossain Lipu MS 3 , Mohamed A 4 , Ker PJ 5 , Indra Mahlia TM 6 Show all authors , Mansor M 5 , Hussain A 4 , Muttaqi KM 7 , Dong ZY 8

Affiliations 

  • 1 Department of Electrical Power Engineering, College of Engineering, Universiti Tenaga Nasional, Kajang, 43000, Malaysia. hannan@uniten.edu.my
  • 2 General Company of Electricity Production Middle Region, Ministry of Electricity, Baghdad, 10001, Iraq
  • 3 Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, 43600, Malaysia. lipu@ukm.edu.my
  • 4 Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, 43600, Malaysia
  • 5 Department of Electrical Power Engineering, College of Engineering, Universiti Tenaga Nasional, Kajang, 43000, Malaysia
  • 6 School of Information, Systems and Modelling, University of Technology Sydney, Ultimo, NSW, 2007, Australia
  • 7 School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW, 2522, Australia
  • 8 School of Electrical Engineering and Telecommunications, UNSW, Kensington, NSW, 2033, Australia
Nat Commun, 2020 Jul 30;11(1):3792.
PMID: 32733048 DOI: 10.1038/s41467-020-17623-5

Abstract

Three-phase induction motors (TIMs) are widely used for machines in industrial operations. As an accurate and robust controller, fuzzy logic controller (FLC) is crucial in designing TIMs control systems. The performance of FLC highly depends on the membership function (MF) variables, which are evaluated by heuristic approaches, leading to a high processing time. To address these issues, optimisation algorithms for TIMs have received increasing interest among researchers and industrialists. Here, we present an advanced and efficient quantum-inspired lightning search algorithm (QLSA) to avoid exhaustive conventional heuristic procedures when obtaining MFs. The accuracy of the QLSA based FLC (QLSAF) speed control is superior to other controllers in terms of transient response, damping capability and minimisation of statistical errors under diverse speeds and loads. The performance of the proposed QLSAF speed controller is validated through experiments. Test results under different conditions show consistent speed responses and stator currents with the simulation results.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

Similar publications