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Control of BLDC motor using MRPID controller with modified landsman converter

Control of BLDC motor using MRPID controller with modified landsman converter The principal intention behind the activity is to regulate the speed, current and commutation of the brushless DC (BLDC) motor. Thereby, the authors can control the torque.Design/methodology/approachIn order to regulate the current and speed of the motor, the Multi-resolution PID (MRPID) controller is proposed. The altered Landsman converter is utilized in this proposed suppression circuit, and the obligation cycle is acclimated to acquire the ideal DC-bus voltage dependent on the speed of the BLDC motor. The adaptive neuro-fuzzy inference system-elephant herding optimization (ANFIS-EHO) calculation mirrors the conduct of the procreant framework in families.FindingsBrushless DC motor's dynamic properties are created, noticed and examined by MATLAB/Simulink model. The performance will be compared with existing genetic algorithms.Originality/valueThe presented approach and performance will be compared with existing genetic algorithms and optimization of different structure of BLDC motor. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Intelligent Computing and Cybernetics Emerald Publishing

Control of BLDC motor using MRPID controller with modified landsman converter

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1756-378X
DOI
10.1108/ijicc-05-2021-0085
Publisher site
See Article on Publisher Site

Abstract

The principal intention behind the activity is to regulate the speed, current and commutation of the brushless DC (BLDC) motor. Thereby, the authors can control the torque.Design/methodology/approachIn order to regulate the current and speed of the motor, the Multi-resolution PID (MRPID) controller is proposed. The altered Landsman converter is utilized in this proposed suppression circuit, and the obligation cycle is acclimated to acquire the ideal DC-bus voltage dependent on the speed of the BLDC motor. The adaptive neuro-fuzzy inference system-elephant herding optimization (ANFIS-EHO) calculation mirrors the conduct of the procreant framework in families.FindingsBrushless DC motor's dynamic properties are created, noticed and examined by MATLAB/Simulink model. The performance will be compared with existing genetic algorithms.Originality/valueThe presented approach and performance will be compared with existing genetic algorithms and optimization of different structure of BLDC motor.

Journal

International Journal of Intelligent Computing and CyberneticsEmerald Publishing

Published: Oct 4, 2021

Keywords: Brushless DC (BLDC) motors; Elephant herding optimization (EHO); Adaptive neuro-fuzzy inference system (ANFIS); Landsman converter

References