Neural approach for speed estimation in induction motors

Abstract

The use of sensorless technologies is an increasing tendency on industrial drives for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables involved in this process. The cost reduction may also be considered in industrial drives, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of artificial neural networks to estimate one of the most important variables in the induction motor control schemes: the speed. Simulation and experimental results are presented to validate the proposed approach.