Intelligent Adaptation Mechanism of Full-Order Luenberger Observer based on Fuzzy Logic Applied to Direct Control by Flux Orientation without Speed Sensor for Doubly Fed Induction Motor

Abstract

The present work focused on the control by flow orientation without mechanical sensors on the doubly fed induction motor by the use of artificial intelligence techniques. Our main contribution lies in the development of control methodologies to improve control by flux orientation, for this, we acted on the type and control of inverters by the use of multilevel inverters and then on the observation technique of rotor speed based on the high gain Luenberger observer and improvements to the speed adaptation mechanism using fuzzy logic. Simulation tests of the proposed improvement approach were carried out at the end of this work to verify the behavior of this system in the face of different types of training.