摘要
针对压电陶瓷执行器的迟滞非线性特性问题,该文提出了一种最小二乘法与径向神经网络相结合的建模方法。首先,通过搭建压电执行器位移测试系统,得到执行器输出位移与输入电压的对应曲线关系,然后用最小二乘法对该曲线进行多项式拟合,得到压电执行器的迟滞数学模型,在此基础上再用径向基函数神经网络方法对该模型进行优化。最后对建立的模型进行分析发现,用最小二乘法拟合的多项式数学模型,其最大误差Emax=0.244 7μm,标准方差δ=0.059 02μm,而利用径向基函数(RBF)神经网络优化建模后,Emax=0.079 89μm,δ=0.016 04μm。实验证明该模型有较高的准确性,该文为压电执行器迟滞建模提供了一种新的方法。
Aiming at the hysteretic nonlinearity of piezoelectric actuator,a modeling method combining least square method with radial neural network is proposed in this paper.Firstly,by setting up the test system of the piezoelectric actuator displacement,the corresponding curve relationship between the output displacement of the actuator and the input voltage is obtained.Then the polynomial fitting of the curve is carried out by least square method to obtain the hysteresis mathematical model of the piezoelectric actuator.On this basis,the radial basis function neural network method is used to optimize the model.Finally,the established model is analyzed.It is found that the maximum error Emaxis equal to 0.244 7μm and the standard deviationδis equal to 0.059 02μm by using the polynomial mathematical model fitted by the least square method,while the maximum error Emaxis equal to 0.079 89μm and the standard deviationδis equal to 0.016 04μm after optimizing by RBF neural network modeling.The experiment verifies that the model has higher accuracy.This paper provides a new method for modeling of the piezoelectric actuators hysteresis.
作者
胡力
李国平
吕雪军
吕俊智
罗展鹏
HU Li;LI Guoping;LYU Xuejun;LYU Junzhi;LUO Zhanpeng(School of Mechanical Engineering and Mechanics,Ningbo University,Ningbo 315211,China)
出处
《压电与声光》
CAS
CSCD
北大核心
2018年第5期695-699,共5页
Piezoelectrics & Acoustooptics
基金
浙江省自然科学基金资助项目(No.LY15E050005)
