Neural learning algorithm based rotor resistance estimation for fuzzy logic based sensorlless IFOC of induction motor

This paper presents the MatlabbbSimulation of fuzzy logic based Sensorless sindirect vector control of induction motor with a rotor resistance adaptation scheme using Neural Learning Algorithm. Here the fuzzy controller offers superior transient performance when compared with the conventional contro...

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Bibliographic Details
Published inEPSCICON : 2014 International Conference on Power Signals Control and Computations : 6-11 January 2014 pp. 1 - 6
Main Author Chandran, Sreedev
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2014
Subjects
Estimation
Fuzzy logic
Fuzzy logic Controller
Indirect Field orientation control
Induction motors
Mathematical model
MRAS Approach
Neural Learning Algorithm
Resistance
Rotor Resistance estimation
Rotors
Sensorless Contro Vector Control
Torque
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DOI10.1109/EPSCICON.2014.6887479

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Summary:This paper presents the MatlabbbSimulation of fuzzy logic based Sensorless sindirect vector control of induction motor with a rotor resistance adaptation scheme using Neural Learning Algorithm. Here the fuzzy controller offers superior transient performance when compared with the conventional control algorithms using PI controller. Rotor resistance of the motor changes significantly with temperature and frequency. This variation has a major influence on the field oriented control performance of an induction motor due to the deviation of slip frequency from the set value. This paper also uses neural learning algorithm for adaptation in a MRAS based rotor resistance estimator for making the robust against rotor resistance variation.
DOI:10.1109/EPSCICON.2014.6887479