Neural Network-Based Model Reference Adaptive System for Torque Ripple Reduction in Sensorless Poly Phase Induction Motor Drive

Neural Network-Based Model Reference Adaptive System for Torque Ripple Reduction in Sensorless Poly Phase Induction Motor Drive

This paper proposes the modified, extended Kalman filter, neural network-based model reference adaptive system and the modified observer technique to estimate the speed of a five-phase induction motor for sensorless drive. The proposed method is generated to achieve reduced speed deviation and reduc...

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Bibliographic Details
Main Authors: S. Usha, C. Subramani, Sanjeevikumar Padmanaban
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Energies
Subjects:
induction motor
speed estimation
model reference adaptive system
kalman filter
luenberger observer
Online Access:http://www.mdpi.com/1996-1073/12/5/920

Internet

http://www.mdpi.com/1996-1073/12/5/920

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