Permanent magnet synchronous motor parameter identification and current prediction control method based on RBF neural network

The invention discloses a permanent magnet synchronous motor parameter identification and current prediction control method based on an RBF neural network. According to the method, an RBF neural network online identifier is designed to estimate the parameters of the permanent magnet synchronous motor, specifically, the output of a full-rank identification model is taken as reference input, and then the output of the full-rank identification model and the output of the RBF neural network are utilized to construct an error adjustment strategy so as to realize parameter identification of the permanent magnet synchronous motor; the parameters of the current prediction controller are updated in real time by using the identified parameters, and the stability of the method is proved by using a discrete Lyapunov function. According to the control method provided by the invention, the problem of response current loss of the permanent magnet synchronous motor caused by mismatching of the control parameters can be effec