Speed Control of Stepping Motor Based on Fuzzy RBF Neural Network
GUO Ziyu
HONG Yingping
ZHANG Huixin
Abstract：Stepping motor is widely used in various industrial occasions due to its low cost and simple operation.In order to solve the problems of slow response speed and high overshoot of two-phase hybrid stepping motor under traditional PID control,a PID control strategy based on fuzzy radial basis function(RBF)neural network is proposed.Firstly,the mathematical model and transfer function of two-phase hybrid stepping motor are deduced theoretically.Then,on the basis of fuzzy PID control,a fuzzy PID control strategy based on RBF neural network is proposed,which is simulated in Matlab Simulink to realize the speed control of the stepping motor.Finally,the speed control experiment platform of two-phase hybrid stepping motor based on STM32 is built,and the proposed control strategy is tested.The experimental results show that the fuzzy RBF neural network controller,which effectively combines fuzzy PID and RBF neural network,realizes the real-time tuning output of PID parameters,has higher control accuracy,higher response speed and smaller overshoot in the control of two-phase hybrid stepping motor,and is an effective control algorithm.
Keywords：stepping motorRBF neural networkPID controlSimulink simulation
Publication Date：2023-12-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 56-61 )