Speed neuro-fuzzy estimator for sensorless indirect flux oriented induction motor drive

Abstract

The wide use of induction motors in high-precision drives calls for more advanced control architectures. Probably the greatest progress made in recent years is the field oriented control (FOC) which allowed the induction motor to move beyond the variable-speed control of Volts per Hertz drives. This work proposes the development of an adaptive neuro-fuzzy inference system (ANFIS) angular rotor speed estimator applied to a FOC sensorless drive. A multi-frequency training of ANFIS is proposed, initially for a volts per hertz scheme and when the best inputs of ANFIS were chosen a drive system with magnetizing flux oriented control was proposed using the ANFIS estimator. Simulations to evaluate the performance of the estimator considering the volts per hertz and vector drive system were realized using the Matlab/Simulink® software. Finally experimental results are presented to validate the ANFIS estimator.