Title :
Neural learning algorithm based rotor resistance estimation for fuzzy logic based sensorlless IFOC of induction motor
Author :
Chandran, Saravanan
Abstract :
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.
Keywords :
PI control; control engineering computing; electric resistance; fuzzy control; induction motors; machine vector control; neural nets; rotors; sensorless machine control; MRAS based rotor resistance estimator; PI controller; field oriented control performance; fuzzy controller; fuzzy logic based sensorless IFOC; induction motor; neural learning algorithm based rotor resistance estimation; sensorless indirect vector control; transient performance; Estimation; Fuzzy logic; Induction motors; Mathematical model; Resistance; Rotors; Torque; Fuzzy logic Controller; Indirect Field orientation control; MRAS Approach; Neural Learning Algorithm; Rotor Resistance estimation; Sensorless Contro Vector Control;
Conference_Titel :
Power Signals Control and Computations (EPSCICON), 2014 International Conference on
Conference_Location :
Thrissur
Print_ISBN :
978-1-4799-3611-3
DOI :
10.1109/EPSCICON.2014.6887479