›› 2012, Vol. ›› Issue (03): 714-718.

• 论文 • 上一篇    下一篇

磁控形状记忆合金执行器迟滞非线性模型

周淼磊, 高巍, 高琳琳, 刘富   

  1. 吉林大学 通信工程学院, 长春 130022
  • 收稿日期:2011-04-07 出版日期:2012-05-01
  • 基金资助:
    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).

Hysteresis model of magnetic shape memory alloy actuator

ZHOU Miao-lei, GAO Wei, GAO Lin-lin, LIU Fu   

  1. College of Communication Engineering, Jilin University, Changchun 130022, China
  • Received:2011-04-07 Online:2012-05-01

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0.0015 mm,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(MSMA)执行器的迟滞非线性模型,并可以获得较高的模型精度。

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

Abstract: 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.

Key words: automatic control technology, magnetic shape memory alloy, PI model, hysteresis nonlinearity

中图分类号: 

  • TP13
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