An ANN strategy applied to induction motor speed estimator in closed-loop scalar control

This work proposes an artificial neural network approach to estimate the induction motor speed applied in a closed-loop scalar control. The induction motor speed is the important quantity in an industrial process. However, the direct measurement of speed compromises the driver system and control, besides increasing the implementation cost. The proposed strategy estimates the induction motor speed when it is driven by voltage source inverter with slip-control. Simulation results are presented to validate the performance of the proposed method under motor load torque and speed reference point variations.