International Journal of Engineering Research in Electrical and Electronic Engineering(IJEREEE)

Monthly Journal for Electrical and Electronic Engineering

International Journal of Engineering Research in Electrical and Electronic Engineering

Volume3 ,November 2016.

Volume3,November 2016,

Topic : ANN Control And Comparitive Methods for Analogue Switched Reluctance Motor Drives

Authors:Malini K V || K.Gopinath, M. Savitha, Yeshwanth. S, Sai Prasad K V

Abstract:The Switched reluctance motor is a well known motor for its ruggedness, simple structure, adoptability and inexpensive manufacturing. This paper presents a suitable way of the drive using ANN method of switching. Its linear model switching and characteristics makes the drive suitable for different methods of drive control. Its dynamics, parameters and control characteristics are discussed in detail. The artificial neural network gives the possibility of controlling the drive for various conditions. This paper discussed the methods of control of SRM in various ways and compares the methods. Artificial Neural Networks are computational models used to obtain complex nonlinear relationships between input and output variables. It is one of the powerful modeling techniques, based on a statistical approach, presently adopted in the field of engineering, The key methods of fuzzy logic and ANN mapping by adjusting the controller gain.The scaling factor fine tuned to give tuning mechanism. The reduction in the number of fuzzy sets of controllers improves the characteristics and thereby reduces the number of sets..

Keywords: Artificial Neural Network, Switched reluctance motor. Comparitives, Fuzzy Logic controller, Variable speed , drives & control

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DOI: 01.1617/vol2iss11pid178


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Editor-in-Chief

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Editor-in-Chief
Dr.Krzysztof Chwastek
Associate Professor,
Czestochowa University of Technology, Polland.


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IMPACT FACTOR: 3.784

ISSN(Online): 2395-2717

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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Journal Code : IJEREEE
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