单细胞分析仪中步进电机的定位控制

Research on Stepper Motor Positioning Control of Single Cell Instrument

该文针对单细胞分析仪器定位控制中步进电机运行时的非线性特性,首先建立了步进电机的数学模型。利用建立的模型,在传统PID控制方法的基础上,设计了一种RBF神经网络与PID相结合的控制方法,并通过RBF神经网络整定PID控制器的参数。为了解决RBF神经网络权值、基宽和中心矢量的初值选取问题,采用遗传算法对初值进行选取,优化神经网络。最后在Matlab/Simulink平台上对所设计的控制方法进行仿真实验,仿真实验结果表明:所设计的控制方法响应时间短、无超调、定位效果好,能较好地满足仪器定位精度的要求。

This paper for the non-linear characteristics of stepper motor positioning control which apply in signal cell detection instrument,a mathematical model of the stepper motor was established.By using the established model,and on the basis of the traditional PID control method,a control method of RBF neural network combined with PID control was designed.The parameters of the PID controllers was tuning through RBF neural network.In order to solve the initial value selection problem of RBF neural network such as weights,width and center vector and optimize the RBF neural network,the genetic algorithms was used. Finally the Matlab/Simulink platform was used to do the simulation experiments of the design control method,by comparing the experimental results,the control method involved short response time,no overshoot,good positioning effect,which can better meet the requirements of positioning precision.