A neural speed estimator in Three-Phase Induction Motors powered by a driver with scalar control

This work proposes an artificial neural network approach to estimate the induction motor speed. The induction motor has a great importance in many industrial sectors in which most control strategies are based on speed measurement of the motor axis. However, the direct measurement of this quantity reduces its robustness, compromises the driver system and control, besides increasing the implementation cost. The presented strategy estimates the induction motor speed when it is driven using scalar control. Simulation results are shown to verify the performance of the proposed method when the induction motor is submitted to load torque variations.