Modeling of a magneto-rheological (MR) fluid damper using a self tuning fuzzy mechanism
Islam, Muhammad Aminul, Ahn, Kyoung Kwang , & Truong, Dinn Quang (2009) Modeling of a magneto-rheological (MR) fluid damper using a self tuning fuzzy mechanism. Journal of Mechanical Science and Technology, 23(5), pp. 1485-1499.
A magneto-rheological (MR) fluid damper is a semi-active control device that has recently begun to receive more attention in the vibration control community. However, the inherent nonlinear nature of the MR fluid damper makes it challenging to use this device to achieve high damping control system performance. Therefore the development of an accurate modeling method for a MR fluid damper is necessary to take advantage of its unique characteristics. Our goal was to develop an alternative method for modeling a MR fluid damper by using a self tuning fuzzy (STF) method based on neural technique. The behavior of the researched damper is directly estimated through a fuzzy mapping system. In order to improve the accuracy of the STF model, a back propagation and a gradient descent method are used to train online the fuzzy parameters to minimize the model error function. A series of simulations had been done to validate the effectiveness of the suggested modeling method when compared with the data measured from experiments on a test rig with a researched MR fluid damper. Finally, modeling results show that the proposed STF interference system trained online by using neural technique could describe well the behavior of the MR fluid damper without need of calculation time for generating the model parameters.
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|Item Type:||Journal Article|
|Keywords:||Magneto-Rheological (MR) Fluid, Damper, Modeling, Self Tuning, Fuzzy|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Automation and Control Engineering (091302)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright KSME & Springer 2009|
|Copyright Statement:||The original publication is available at SpringerLink http://www.springerlink.com|
|Deposited On:||11 Nov 2011 11:10|
|Last Modified:||27 Mar 2013 01:11|
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