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Title: Modified Reference Model for Rotor Flux-Based MRAS Speed Observer Using Neural Network Controller
Authors: Giribabu D.
Srivastava S.P.
Pathak, M. K.
Published in: IETE Journal of Research
Abstract: The poor low speed performance of rotor flux-based model reference adaptive system (MRAS) is due to the presence of integrator and parameter variation with temperature. To improve low speed performance, a novel rotor flux-based MRAS method is proposed and neural network controller (NNC) is used in place of PI controller in reference model and adaptation mechanism. In this method, a compensating voltage is added to the d–q axis rotor flux equations of induction motor (IM) by modifying voltage model to reduce DC drift and initial value problems of integrator. NNC is implemented in both modified reference model to obtain the drift voltage and in adaptation mechanism to accurately estimate the rotor speed. The proposed scheme is experimentally implemented using dSPACE ds-1104 R&D controller board with improved speed response compared to rotor flux-based MRAS. © 2017, © 2017 IETE.
Citation: IETE Journal of Research (2019), 65(1): 80-95
Issue Date: 2019
Publisher: Taylor and Francis Ltd
Keywords: Induction motor
Model reference adaptive system
Neural networks
Vector control
ISSN: 3772063
Author Scopus IDs: 55220167200
Author Affiliations: Giribabu, D., Department of Electrical Engineering, National Institute of Technology, Kurukshetra, India
Srivastava, S.P., Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India
Pathak, M.K., Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India
Appears in Collections:Journal Publications [EE]

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