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Altered PPI Due to Mutations in hPER2 and CKI Delta Locus, Causing ASPS Read chapter Read first chapter

2017 | OriginalPaper | Chapter

An Improved Stator Resistance Adaptation Mechanism in MRAS Estimator for Sensorless Induction Motor Drives

Authors : S. Mohan Krishna, J. L. Febin Daya

Published in: Proceedings of the First International Conference on Intelligent Computing and Communication

Publisher: Springer Singapore

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Abstract

A comparative study of the conventional fixed gain PI and Fuzzy Logic based adaptation mechanisms for estimating the stator resistance in a Model Reference Adaptive System (MRAS) based sensorless induction motor drive is investigated here. The rotor speed is estimated parallely by means of a PI control based adaptive mechanism and the electromagnetic torque is also estimated to add more resilience. By considering the external Load torque perturbation as a model perturbation on the estimated stator resistance, the effects of the same on the estimated parameters are observed. The superiority of the Fuzzy based stator resistance adaptation mechanism is observed through detailed simulation performed offline using Matlab/Simulink blocksets. Furthermore, a sensitivity analysis of the stator resistance estimate with respect to load torque is also done to verify the effectiveness of the above concept.

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Appendix
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Metadata
Title
An Improved Stator Resistance Adaptation Mechanism in MRAS Estimator for Sensorless Induction Motor Drives
Authors
S. Mohan Krishna
J. L. Febin Daya
Copyright Year
2017
Publisher
Springer Singapore
Book
Proceedings of the First International Conference on Intelligent Computing and Communication

Print ISBN: 978-981-10-2034-6

Electronic ISBN: 978-981-10-2035-3

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-2035-3_38

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