NDLI: Artificial Neural Network Based Rotor Position Estimation for Switched Reluctance Motor

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Artificial Neural Network Based Rotor Position Estimation for Switched Reluctance Motor

Content Provider	Scilit
Author	Shanthi L, Jessi Sahaya Arumugam, R. Taly, Y.K. Kumar, S.B. Nandha
Copyright Year	2008
Description	Switched Reluctance Motor (SRM) is becoming popular as a variable speed industrial drive. But the requirement of position sensor to synchronize the rotor position with phase currents makes the SRM drive circuit complex and unreliable. With the advent of high speed digital signal processors, it is possible to implement algorithms to estimate the rotor position based on the electrical signals in motor windings. In addition to this, the latest graphical user interface software aids to reduce the time for the development of control algorithms. This paper presents the simulation study of an artificial neural network(ANN) based algorithm for rotor position estimation from phase voltage and current of a four phase SRM using VISSIM version 6.0B software. Based on the simulation results, a particular artificial neural network (ANN) is selected and checked for real time implementation.
ISSN	19131844
e-ISSN	19131852
DOI	10.5539/mas.v2n6p148
Alternate Webpage(s)	http://ccsenet.org/journal/index.php/mas/article/download/2137/2006
Journal	Modern Applied Science
Issue Number	6
Volume Number	2
Language	English
Publisher	Canadian Center of Science and Education
Publisher Date	2008-11-17
Access Restriction	Open
Subject Keyword	Hardware and Architecture Switched Reluctance Motor Artificial Neural Network Rotor Position Estimation
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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