Research of brushless DC motor control system based on RBF neural network

Brushless DC motor (BLDCM) with non-linear, strong coupling and other advantages are widely used in various occasions. Aiming at the shortcomings of low precision and poor robustness of conventional PID brushless DC motor controller, a brushless DC motor control system based on RBF neural network is designed by analyzing the mathematical model of BLDCM. The simulation results show that compared with the conventional PID control method, this method can greatly improve the dynamic characteristics of the control system and reduce the steady-state error of the system, so as to improve the system's adaptive ability and anti-jamming capability, To meet the system requirements for control performance.