Sensorless control of permanent magnet synchronous motorparameter optimization

The sensorless control of the PMSM depends on the rotor position observer, and the accuracy of the observer directly affects the control of the motor. In order to solve the complex problem of the parameter setting process in the rotor position observer, this paper proposes a method to optimize the rotor position observer based on the error back-propagation (BP) neural network, and uses the proposed error back-propagation (BP) neural network to optimize the parameters of the rotor position observer to realize the sensorless optimal control of permanent magnet synchronous motor. It is proved by MATLAB/Simulink that BP neural network can calculate the parameters of rotor position observer quickly and accurately by comparing with traditional formula setting method.