Please use this identifier to cite or link to this item: http://dspace.aiub.edu:8080/jspui/handle/123456789/295
Title: Comparative Analysis between Conventional PI, Fuzzy Logic and Artificial Neural Network Based Speed Controllers of Induction Motor with Considering Core Loss and Stray Load Loss
Authors: Hazari, Md. Rifat
Jahan, Effat
Mannan, Mohammad Abdul
Tamura, Junji
Issue Date: 15-Jan-2017
Publisher: Journal of Mechanics Engineering and Automation, David Publisher
Abstract: Most of the controllers of IM (induction motor) for industrial applications have been designed based on PI controller without consideration of CL (core loss) and SLL (stray load loss). To get the precise performances of torque as well as rotor speed and flux, the above mentioned losses should be considered. Conventional PI controller has overshoot effect at the transient period of the speed response curve. On the other hand, fuzzy logic and ANN (artificial neural network) based controllers can minimize the overshoot effect at the transient period because they have the abilities to deal with the nonlinear systems. In this paper, a comparative analysis is done between PI, fuzzy logic and ANN based speed controllers to find the suitable control strategy for IM with consideration of CL and SLL. The simulation analysis is done by using Matlab/Simulink software. The simulation results show that the fuzzy logic based speed controller gives better responses than ANN and conventional PI based speed controllers in terms of rotor speed, electromagnetic torque and rotor flux of IM.
URI: http://dspace.aiub.edu:8080/jspui/handle/123456789/295
Appears in Collections:Publications From Faculty of Engineering

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