Sensorless control of the permanent magnet synchronous motor using neural networks

In this paper, a neural network based rotor position control and speed estimation method for permanent magnet synchronous motor (PMSM) is proposed. The proposed method has three recurrent neural networks. They are used for estimating stator current, rotor speed, and rotor position angle. Each of them is trained in two steps: off-line training for learning dynamic of PMSM and on-line training for realizing parameter adaptation of PMSM. Sensorless control of the permanent magnet synchronous motor using neural networks is simulated in Matlab/Simulink.