Non-parametric modeling of a magneto-rheological (MR) damper based on adaptive neuro-fuzzy inference system

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Journal of Vibration and Shock ›› 2011, Vol. 30 ›› Issue (10) : 25-29.

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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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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.

Key words

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

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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