Study on Adaptive Speed Recognition of Permanent Magnet Synchronous Motor by Recurrent Neural Network

The variation of the internal parameters of the motor will greatly affect the results of the conventional permanent magnet synchronous motor speed recognition. To address this problem, this paper proposes an adaptive speed recognition model based on recursive neural network. Such networks have a strong ability to handle transient information and can solve the problem of nonlinear dynamic identification and control. By using the Simulink module and the S function to establish a simulation model to analyze its performance, the method has a very fast convergence speed, good responsiveness to the speed identification, can accurately track the speed change trajectory, and still has a stable dynamic performance when the motor parameters change greatly.