Journals / Turkish Journal of Electrical Engineering and Computer Science / 2016 / Cilt: 24 - Sayı: 5

Reduction of torque ripple in induction motor by artificial neural multinetworks

Pages
3492–3502
Publication Date
2016-10-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The experimental results also show that the proposed method would be a good alternative to the conventional method in induction motors.

📌 3 Key Takeaways

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Objective & Hypothesis:Direct torque control is used in the high performance control of induction motors.
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Key Findings & Data:The most frequently faced problem of it is high torque ripples.
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Conclusion & Impact:The experimental results also show that the proposed method would be a good alternative to the conventional method in induction motors.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Direct torque control · induction motor · neural networks

Abstract

Direct torque control is used in the high performance control of induction motors. The most frequently faced problem of it is high torque ripples. In this study, a new approach based on artificial neural multinetworks is presented to overcome the problem. Two different artificial neural networks were suggested instead of vector selection and sector determination processes in the conventional direct torque control method. The conventional and the proposed control methods were evaluated on an induction motor through an experimental set. It was observed that the speed and torque responses of the proposed method were better than those of the conventional method. The experimental results also show that the proposed method would be a good alternative to the conventional method in induction motors.

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Cite This Article

KORKMAZ, F., TOPALOĞLU, İ., MAMUR, H., ARI, M., TARIMER, İ. (2016). Reduction of torque ripple in induction motor by artificial neural multinetworks. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 24 - Sayı: 5, 3492–3502. https://ajindex.com/articles/188302

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