Speed Estimation of an Induction Motor with Sensorless Vector Control at Low Speed Range Using Neural Networks

This paper deals with the study, design and implementation of a speed estimation technique, using an Artificial Neural Network (ANN), for a three-phase induction motor type Squirrel Cage. The main objective of this technique is to estimate the speed of the engine from its own conditions at low speed, with the purpose of applying vector control without the use of a traditional speed sensor that supplies the control loop with the speed of rotation the motor. When replacing the traditional sensor with RNA, a sensorless control loop is obtained. The training of the RNA was done collecting data in different ranges of engine speed, both empty and loaded. The simulation of the system is carried out in the Simulink platform, from the Matlab software package and the implementation of the control strategy is done using the Raspberry Pi 3B card.