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Direct control of asynchronous motor torque with neuro-fuzzy speed regulator and neural network identification of electrical drive parameters

https://doi.org/10.30724/1998-9903-2015-0-1-2-95-101

Abstract

We considered a modified system for a direct control of induction motor torque using a neural network unit for identification of electrical drive parameters. A number of disadvantages for the standard torque control system were identified. We described neural network element synthesis, in order to modify the system and overcome these disadvantages. Our modeling results for the modified system with neural network and neural-fuzzy components are presented.

About the Authors

A. A. Shigapov
Казанский государственный энергетический университет
Russian Federation


B. P. Smolyakov
Казанский государственный энергетический университет
Russian Federation


References

1. Wang Ping, Li Bin, Huang Ruixiang, Li Guidan. Diangong jishu xuebaoTrans. China Electrotech. Soc. 2003. 18, № 2, P.5-8

2. Kusuma Gottapu1 ,YV Prashanth 2,P Mahesh3 , Y Sumith. Simulation of DTC IM Based on PI& Artificial Neural Network Technique. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering Vol. 2, Issue 7, July 2013

3. Mamdani E.H. and Assilian S. An experiment in linguistic synthesis with a fuzzy logic controller // Int. J. Man-Mach. Stud. 1975. Vol. 7. P. 1-13.


Review

For citations:


Shigapov A.A., Smolyakov B.P. Direct control of asynchronous motor torque with neuro-fuzzy speed regulator and neural network identification of electrical drive parameters. Power engineering: research, equipment, technology. 2015;(1-2):95-101. (In Russ.) https://doi.org/10.30724/1998-9903-2015-0-1-2-95-101

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ISSN 1998-9903 (Print)
ISSN 2658-5456 (Online)