Volume 1 Number 2 (Jun. 2009)
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IJCEE 2009 Vol.1 (2): 236-244 ISSN: 1793-8163
DOI: 10.7763/IJCEE.2009.V1.37

ANN Based Flux and Torque Estimator for Vector Controlled Induction Drive with Dynamic Loading

D. D. Neema, R. N. Patel, and A. S. Thoke

Abstract—Vector control of induction motor drives is very useful technique to obtain high performance speed response. Implementation of vector control requires the knowledge of instantaneous magnitude and position of rotor flux and load behavior in the shaft for correct dimensioning of an induction motor. This paper demonstrates estimation of feedback signals in a three phase induction motor derive under dynamic load conditions using Artificial Neural Network (ANN). A instantaneous magnitude and position of rotor flux and load torque estimator, in the form of a two stage neural network is presented. The neural network is able to accurately estimate these parameters of an induction motor. The observations indicate that ANN based flux and load torque estimation may be a feasible alternative to other rotor flux and load torque estimation methods like programmable DSP kit. The comparative performance of both has been presented in this work with the help of a practical three-phase induction motor drive.

Index Terms—Back propagation, DSP, FOC, Induction drive, Neural network, Vector control.

D. D. Neema is with the dept. of Electrical Engineering, RCET, Bhilai (C.G.), India
R. N. Patel is with the dept. of Electrical Engineering, SSCET, Bhilai (C.G.), India, (Corresponding Author: Phone: +91-9827494379)
 A. S. Thoke is with the dept. of Electrical Engineering, NIT Raipur (C.G.), India

Cite: D. D. Neema, R. N. Patel and A. S. Thoke, "ANN Based Flux and Torque Estimator for Vector Controlled Induction Drive with Dynamic Loading," International Journal of Computer and Electrical Engineering vol. 1, no. 2, pp. 236-244, 2009.

General Information

ISSN: 1793-8163 (Print)
Abbreviated Title: Int. J. Comput. Electr. Eng.
Frequency: Quarterly
Editor-in-Chief: Prof. Yucong Duan
Abstracting/ Indexing: EI (INSPEC, IET), Ulrich's Periodicals Directory, Google Scholar, EBSCO, ProQuest, and Electronic Journals Library
E-mail: ijcee@iap.org

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