Neural Learning Algorithm Based Rotor Resistance Estimation For Fuzzy Logic Based Sensorless IFOC of Induction Motor

This paper presents the Matlab Simulation of fuzzy logic based Sensorless indirect 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.