| 对Preisach类的迟滞非线性神经网络建模 |
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| 引用本文： | 赵新龙,谭永红.对Preisach类的迟滞非线性神经网络建模[J].控制理论与应用,2006,23(4):581-585. |
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| 作者姓名： | 赵新龙 谭永红 |
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| 作者单位： | 1. 上海交通大学,电子信息学院,自动化系,上海,200030
2. 桂林电子科技大学,智能系统与工业控制研究室,广西,桂林,100080 |
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| 基金项目： | 国家自然科学基金资助项目(50265001,60572055); 广西自然科学基金资助项目(0339068) |
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| 摘 要： | 为了消除迟滞非线性对系统的不良影响,本文利用神经网络对Preisach类的迟滞非线性进行建模．通过引入一个特殊的迟滞因子,将多映射的迟滞非线性转换成一一映射,然后建立了基于神经网络的迟滞非线性模型．该模型结构简单,简化了辨识过程,可以调整神经网络权值以适应不同条件下的迟滞辨识．最后．应用该方法对压电执行器中的迟滞非线性建模,并与KP模型进行了比较．
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| 关 键 词： | 迟滞 Preisach模型 神经网络 |
| 文章编号： | 1000-8152（2006）04-0581-05 |
| 收稿时间： | 2004-10-27 |
| 修稿时间： | 2004-10-272005-12-07 |
Modeling Preisach-type hysteresis nonlinearity using neural networks |
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| ZHAO Xin-long,TAN Yong-hong.Modeling Preisach-type hysteresis nonlinearity using neural networks[J].Control Theory & Applications,2006,23(4):581-585. |
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| Authors: | ZHAO Xin-long TAN Yong-hong |
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| Affiliation: | Department of Automation, Shanghai Jiao Tong University, Shanghai 200030, China;Laboratory of Intelligent Systems and Control Engineering, Guilin University of Electronic Technology, Guilin Guangxi 541004, China |
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| Abstract: | In order to approximate the behavior of hysteresis nonlinerity which often severely limits the performance of the system, a neural-network-based hysteresis model is presented in this paper. A novel hysteretic operator is firstly proposed to transform the multi-valued mapping of Preisach-type hysteresis into a one-to-one mapping so that the neural networks are capable of implementing identification for hysteresis. The proposed model has a simple structure and simplifies identification procedure. Moreover, it is convenient to tune the weights of neural networks for the identification of hysteresis in different conditions. Finally the approach is applied to model the hysteresis in piezoelectric actuator and compared with the well-known KP model. |
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| Keywords: | hysteresis Preisach model neural networks |
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