基于改进遗传算法优化的双步进电机伺服阀控制研究  

Research on Servo Valve Control of Double Stepping Motor Optimized by Improved Genetic Algorithms

作　　者：郑王刚 孟淑丽[2] 郝雷[3] ZHENG Wanggang;MENG Shuli;HAO Lei(Institute of Intelligent Manufacturing,Xinxiang Vocational and Technical College, Xinxiang Henan 453000,China;School of Engineering and Technology,Beijing Institute of Economics and Management, Beijing 102602,China;School of Electronic and Information Engineering,Hebei University, Baoding Heibei 071002,China)

机构地区：[1]新乡职业技术学院智能制造学院,河南新乡453000 [2]北京经济管理职业学院工程技术学院,北京102602 [3]河北大学电子信息工程学院,河北保定071002

出　　处：《机床与液压》2020年第9期145-149,共5页Machine Tool & Hydraulics

基　　金：河北省自然科学基金资助项目(B2014201008);河北省高等学校科学技术研究项目(Z2015147)。

摘　　要：针对当前电液伺服阀控制系统响应速度慢、输出误差较大的问题,采用改进遗传算法优化控制系统,并对控制效果进行仿真验证。设计了新型电液伺服阀结构,建立了电液伺服系统动力学模型,推导了液压缸流量运动方程式。采用改进遗传算法优化RBF神经网络结构,通过MATLAB软件对双步进电机伺服阀改进的控制系统进行仿真验证,并且与传统PID控制效果进行对比。结果显示:在无干扰环境中,采用传统PID控制和改进RBF神经网络控制方法都能较好地提高活塞杆运动位移输出精度;在有干扰环境中,采用传统PID控制方法,活塞杆运动位移输出的误差较大,而采用改进RBF神经网络控制方法,活塞杆运动位移输出的误差较小。采用改进RBF神经网络控制方法,能够抑制外界的干扰,从而提高双步电机伺服阀控制系统的响应速度和输出精度。Aimed at the problems of slow response speed and large output error of electro-hydraulic servo valve control system,the control system was optimized by improved genetic algorithm,and the control effect was simulated and verified.The structure of a new type electro-hydraulic servo valve was designed,the dynamic model of the electro-hydraulic servo system was established,and the flow motion equation of the hydraulic cylinder was deduced.The improved genetic algorithm was used to optimize the structure of the RBF neural network,and the improved control system of double-step motor servo valve was simulated and verified by MATLAB,and the control effect was compared with that of the traditional PID.The results show that in the non-interference environment,both the traditional PID control method and improved RBF neural network control method can improve the accuracy of piston rod displacement output,while in the environment with interference,the traditional PID control method has a larger error of piston rod displacement output,the improved RBF neural network control method has a smaller error of piston rod displacement output.The improved RBF neural network control method can suppress the external interference,so as to improve the response speed and output precision of the double-step motor servo valve control system.

关 键 词：双步进电机 伺服阀 改进遗传算法 RBF神经网络 控制 

分 类 号：TH137.7[机械工程—机械制造及自动化]