基于自适应神经模糊的磁流变阻尼器非参数化建模

郑玲;周忠永

振动与冲击 ›› 2011, Vol. 30 ›› Issue (10) : 25-29.

PDF(1854 KB)
PDF(1854 KB)
振动与冲击 ›› 2011, Vol. 30 ›› Issue (10) : 25-29.
论文

基于自适应神经模糊的磁流变阻尼器非参数化建模

  • 郑玲; 周忠永
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Non-parametric modeling of a magneto-rheological (MR) damper based on adaptive neuro-fuzzy inference system

  • ZHENG Ling; ZHOU Zhong-yong
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摘要

磁流变阻尼器具有很强的非线性特性,准确描述磁流变阻尼器输入、输出之间的非线性关系,对提高磁流变减振系统的控制精度,保持控制系统稳定性,具有重要意义。针对经典参数化建模存在的大量参数辨识和计算复杂问题,采用自适应神经模糊系统理论,根据磁流变阻尼器实验模型,建立了磁流变阻尼器非参数化模型。它包括两个自适应神经模糊子系统,分别对特定电压下,磁流变阻尼器输入、输出关系以及电压变化导致的阻尼力输出等级进行描述。研究表明:基于自适应神经模糊理论的磁流变阻尼器非参数化模型,能以很高的精度逼近磁流变阻尼器实验模型,真实反映磁流变阻尼器的非线性特性。由于非参数化模型的计算工作量大大减少,有利于实现磁流变减振系统的精确与快速控制。

Abstract

An magneto-rheological (MR) damper is nonlinear typically. The nonlinear relationship between the input and the output of the MR damper should be characterized accurately in order to improve the accuracy of vibration control system with MR dampers and maintain its control stability. The challenge of the conventional parametric modeling is computational complexity and the identification of a large number of parameters. A non-parametric modeling of MR damper based on the adaptive neuro-fuzzy systems theory is presented to overcome the drawback of conventional parametric modeling in this paper. The experimental results from MR damper ( RD-1005 , Lord Company ) are used as reference data to follow. It includes two adaptive neural fuzzy subsystems which describe the relation between the MR damper input and output for specific voltage and voltage change respectively. The results shows that the non-parametric MR damper modeling based on adaptive neuro-fuzzy theory can accurately approach to the experimental model of the MR damper and describe the nonlinear characteristics of the MR damper. This method provides a key technical support for precise control and goal realization of vibration control system with MR dampers due to short calculation process.

关键词

磁流变阻尼器 / 参数化模型 / 非参数化模型 / 自适应神经模糊

Key words

magneto-rheological (MR) damper / parametric model / non-parametric model / adaptive neuro-fuzzy inference system (ANFIS)

引用本文

导出引用
郑玲;周忠永. 基于自适应神经模糊的磁流变阻尼器非参数化建模[J]. 振动与冲击, 2011, 30(10): 25-29
ZHENG Ling;ZHOU Zhong-yong. Non-parametric modeling of a magneto-rheological (MR) damper based on adaptive neuro-fuzzy inference system[J]. Journal of Vibration and Shock, 2011, 30(10): 25-29

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