Direct Torque Control of Induction Motor Based on Neurofuzzy

The main objective of this work is to improve the speed and torque responses of three phase Induction Motor (IM) during different loads and speeds conditions. Induction Motor is most commonly used in different industrial applications, that require fast dynamic response and accurate control over wide...

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Main Authors: Abdulrahim T. Humod, Wiam I. Jabbar
Format: Article
Language:English
Published: Unviversity of Technology- Iraq 2013-10-01
Series:Engineering and Technology Journal
Subjects:
Online Access:https://etj.uotechnology.edu.iq/article_83435_0f4682a612a5b1eec603f417357d91c2.pdf
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author Abdulrahim T. Humod
Wiam I. Jabbar
author_facet Abdulrahim T. Humod
Wiam I. Jabbar
author_sort Abdulrahim T. Humod
collection DOAJ
description The main objective of this work is to improve the speed and torque responses of three phase Induction Motor (IM) during different loads and speeds conditions. Induction Motor is most commonly used in different industrial applications, that require fast dynamic response and accurate control over wide speed ranges. Therefore, this work proposes Direct Torque Control (DTC). Particle Swarm Optimization (PSO) technique is used for optimal gains tuning of PI. The results show the improvement in the speed response of DTC, in terms of reducing steady state error, ripple reduction in the torque and speed responses. Neurofuzzy (ANFIS) controller is used to improve the performance of PI-PSO controller. ANFIS controller is trained by using PI-PSO data. The results of the ANFIS controller are better than PI-PSO in terms of torque ripple minimization, less steady state error in the speed response and more robustness. The simulation of the overall drive system is performed using MATLAB/Simulink program version 7.10 (R2010a).
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spelling doaj.art-7ec8eb2254e64b6599aa578600cb152a2024-02-04T17:36:52ZengUnviversity of Technology- IraqEngineering and Technology Journal1681-69002412-07582013-10-0131173259327310.30684/etj.31.17A.483435Direct Torque Control of Induction Motor Based on NeurofuzzyAbdulrahim T. HumodWiam I. JabbarThe main objective of this work is to improve the speed and torque responses of three phase Induction Motor (IM) during different loads and speeds conditions. Induction Motor is most commonly used in different industrial applications, that require fast dynamic response and accurate control over wide speed ranges. Therefore, this work proposes Direct Torque Control (DTC). Particle Swarm Optimization (PSO) technique is used for optimal gains tuning of PI. The results show the improvement in the speed response of DTC, in terms of reducing steady state error, ripple reduction in the torque and speed responses. Neurofuzzy (ANFIS) controller is used to improve the performance of PI-PSO controller. ANFIS controller is trained by using PI-PSO data. The results of the ANFIS controller are better than PI-PSO in terms of torque ripple minimization, less steady state error in the speed response and more robustness. The simulation of the overall drive system is performed using MATLAB/Simulink program version 7.10 (R2010a).https://etj.uotechnology.edu.iq/article_83435_0f4682a612a5b1eec603f417357d91c2.pdfinduction motordirect torque controlpi controllerparticle swarm optimization
spellingShingle Abdulrahim T. Humod
Wiam I. Jabbar
Direct Torque Control of Induction Motor Based on Neurofuzzy
Engineering and Technology Journal
induction motor
direct torque control
pi controller
particle swarm optimization
title Direct Torque Control of Induction Motor Based on Neurofuzzy
title_full Direct Torque Control of Induction Motor Based on Neurofuzzy
title_fullStr Direct Torque Control of Induction Motor Based on Neurofuzzy
title_full_unstemmed Direct Torque Control of Induction Motor Based on Neurofuzzy
title_short Direct Torque Control of Induction Motor Based on Neurofuzzy
title_sort direct torque control of induction motor based on neurofuzzy
topic induction motor
direct torque control
pi controller
particle swarm optimization
url https://etj.uotechnology.edu.iq/article_83435_0f4682a612a5b1eec603f417357d91c2.pdf
work_keys_str_mv AT abdulrahimthumod directtorquecontrolofinductionmotorbasedonneurofuzzy
AT wiamijabbar directtorquecontrolofinductionmotorbasedonneurofuzzy