Switched reluctance motor doubly salient structure and magnetic circuit of the motor flux is highly saturated highly nonlinear, leading to classical PID control can not get higher control precision. This paper designing of feedforward and feedback controller based on self-adaptive RBF neural network for SRM. The simulation results show that, this method can improve the precision of motor speed, torque pulsation, thereby optimizing the motor operating performance.