磁控形状记忆合金执行器迟滞非线性模型  

Hysteresis model of magnetic shape memory alloy actuator

作　　者：周淼磊[1] 高巍[1] 高琳琳[1] 刘富[1] 

机构地区：[1]吉林大学通信工程学院,长春130022

出　　处：《吉林大学学报（工学版）》2012年第3期714-718,共5页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金项目(51105170);吉林省科技发展计划项目(20090122);吉林大学科学前沿与交叉学科创新项目(200903309)

摘　　要：针对磁控形状记忆合金执行器的迟滞非线性,利用PI模型建模思想,采用线性Play算子建立磁控形状记忆合金执行器迟滞非线性模型。根据其模型结构与神经网络结构十分相似的特点,引入神经网络进行权值训练。为了提高系统的实时性,采用遗忘因子递推最小二乘法训练权值。试验结果显示:本文方法对输出位移的最大预测误差为0.0015mm,均方差为2.2931×10-4,最大误差率为0.1593%,表明该方法能够有效地建立磁控形状记忆合金(MS-MA)执行器的迟滞非线性模型,并可以获得较高的模型精度。In order to solve the hysteresis nonlinearity of magnetic shape memory alloy actuator,a hysteresis model that utilizes the principle of the PI model is proposed.This model is composed of a number of simple linear operators called linear-play operators.As the structure of the model is similar to the structure of the neural network,the method for training the weight of neural network is introduce.In order to improve the real-time characteristic of the control system,forgetting factor recursive least-squares algorithm is adopted to train the weight of the model.Experimental results demonstrate that the modeling error is 0.0015 mm,mean-square deviation is 2.2931×10-4,and the maximal error rate is 0.1593%.The proposed modeling method is effective and could obtain higher accuracy.

关 键 词：自动控制技术 磁控形状记忆合金 PI模型 迟滞非线性 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] TB34[自动化与计算机技术—控制科学与工程]