Advanced Speed Control of Induction Machine Based on Vector Control

This paper presents an advanced speed control of induction machine using fuzzy logic controller (FLC) and artificial neural network controller (ANNC). The proposed strategy is realized by application of indirect rotor flux-oriented control (IRFOC) on squirrel cage induction machine (SCIM) fed by a Pulse- Width Modulated (PWM) inverter. The speed (PI) controller usually causes a fluctuation in the transient state especially in terms of: rise time, settling time, overshot and steady-state error which affects the machine performances. Therefore, in order to overcome this drawback, we have proposed in this paper the use of advanced controllers based on artificial intelligence (AI) techniques. The comparative study of IRFOC with conventional proportional-integral (PI), IRFOC with (FLC) and IRFOC with (ANNC) is carried out by MATLAB/SIMULINK software. The simulation results prove the superiority of the proposed advanced controllers in terms of good performance of the reference tracking dynamics.