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Fuzzy Radius Basis Function neural network based vector control of Permanent Magnet Synchronous Motor

The permanent magnet synchronous motor (PMSM) is a dynamic, multi-variable and non-linear system, and the conventional PID control method is very difficult to meet the requirement for high accuracy control. This paper presents an approach of control for PMSM servo system using fuzzy radius basis function (f-RBF) neural network which has the advantages of strong adaptive ability and nonlinear approximation capability. Combined with vector control scheme, the f-RBF neural network based online identifier and controller is constructed to identify and control system. Simulation and comparison between this approach and conventional PID control to PMSM is taken under Matlab/Simulink. With the presented method, satisfactory response speed and precision as well as good dynamic performance and strong robustness were obtained by experiments.