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

M. A. Hannan (), Jamal Abd. Ali, M. S. Hossain Lipu (), A. Mohamed, Pin Jern Ker, T. M. Indra Mahlia, M. Mansor, Aini Hussain, Kashem M. Muttaqi and Z. Y. Dong
Additional contact information
M. A. Hannan: Universiti Tenaga Nasional
Jamal Abd. Ali: General Company of Electricity Production Middle Region, Ministry of Electricity
M. S. Hossain Lipu: Universiti Kebangsaan Malaysia
A. Mohamed: Universiti Kebangsaan Malaysia
Pin Jern Ker: Universiti Tenaga Nasional
T. M. Indra Mahlia: University of Technology Sydney
M. Mansor: Universiti Tenaga Nasional
Aini Hussain: Universiti Kebangsaan Malaysia
Kashem M. Muttaqi: University of Wollongong
Z. Y. Dong: School of Electrical Engineering and Telecommunications, UNSW

Nature Communications, 2020, vol. 11, issue 1, 1-11

Abstract: 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.

Date: 2020
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DOI: 10.1038/s41467-020-17623-5

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