摘要
步进电机成本低廉,操作简单,被广泛应用于各种工业场合中。为了解决两相混合式步进电机在传统PID控制下的响应速度慢,超调量高等问题,提出一种基于模糊径向基函数(RBF)神经网络的PID控制策略。首先,理论推导计算两相混合式步进电机的数学模型和传递函数;然后,在模糊PID控制的基础上,提出了一种基于RBF神经网络的模糊PID控制策略,在Matlab-Simulink中进行仿真,实现对步进电机的转速控制;最后搭建基于STM32的两相混合式步进电机的转速控制实验平台,对所提出的控制策略进行了试验研究。试验结果表明,将模糊PID和RBF神经网络有效结合的模糊RBF神经网络控制器,实现了PID参数实时整定输出,在两相混合式步进电机的控制中具有较高的控制精度、较高的响应速度和较小的超调量,是一种有效的控制算法。
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.
作者
郭子裕
洪应平
张会新
GUO Ziyu;HONG Yingping;ZHANG Huixin(State Key Laboratory of Electronic Testing Technology,North University of China,Taiyuan 030051;Key Laboratory of Instrument Science and Dynamic Testing,Ministry of Education,Taiyuan 030051)
出处
《舰船电子工程》
2023年第12期56-61,共6页
Ship Electronic Engineering
