Skip navigation
Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/7648
Title: Parallel stator resistance estimator using neural networks for rotor flux based model reference adaptive system speed observer
Authors: Dyanamina G.
Pathak, M. K.
Srivastava S.P.
Published in: Electric Power Components and Systems
Abstract: Model reference adaptive system schemes offer simpler implementation and require less computational effort compared to other speed sensorless methods. The performance of rotor flux based model reference adaptive system schemes at low-speed operation is poor because of parameter sensitivity and presence of the integrator in the reference model. As stator resistance inevitably varies with temperature, for accurate operation at low speeds, an appropriate online identification algorithm for the stator resistance is required. In this article, a neural network based parallel stator resistance and rotor speed estimator has been proposed to simultaneously rectify the limitation of model reference adaptive system schemes, i.e., stator resistance variation and DC offset due to integrator, employing a neutral network in stator resistance estimator and modifying the reference model by adding a compensating voltage term. An indirect sensorless vector control scheme has been simulated and experimentally validated using the dSPACE DS-1104 R&D controller board (dSPACE GmbH, Paderborn, Germany) to verify the performance of drives at different operating conditions. Copyright © Taylor & Francis Group, LLC.
Citation: Electric Power Components and Systems (2016), 44(6): 658-672
URI: https://doi.org/10.1080/15325008.2015.1124157
http://repository.iitr.ac.in/handle/123456789/7648
Issue Date: 2016
Publisher: Taylor and Francis Inc.
Keywords: indirect vector control
induction motor
integrator
low speed
model reference adaptive system
neural networks
sensorless
speed observer
stator resistance estimator
ISSN: 15325008
Author Scopus IDs: 55745558000
37057883200
7403307033
Author Affiliations: Dyanamina, G., Department of Electrical Engineering, National Institute of Technology Kurukshetra, Kurukshetra, Haryana, 136119, India
Pathak, M.K., Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
Srivastava, S.P., Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
Corresponding Author: Dyanamina, G.; Department of Electrical Engineering, National Institute of Technology KurukshetraIndia; email: dgiribabu208@gmail.com
Appears in Collections:Journal Publications [EE]

Files in This Item:
There are no files associated with this item.
Show full item record


Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.