NEURO-FUZZY MODELING OF A SPONGE-TYPE MR DAMPER

Abstract eng:
Numerical modeling of MR dampers based on parametric models constitutes one of the main methodologies to simulate the behavior of this type of devices. However, its highly non-linear nature and also its inherent rheological behavior make this type of numerical modeling harsh and complicated, which hinders the development of simple models capable to cover all aspects associated with the proper numerical simulation of the damper behavior and therefore usually complex parametric models involving several parameters are required to achieve a reliable and accurate representation of its rheological behavior. Hence, nonparametric models represent another feasible approach to simulate the complex non-linear behavior of MR dampers although in this case allowing to obtain a wide-ranging numerical model without the need to define or identify a large number of model parameters. In this context, we attempt to model and predict the response of a sponge-type MR damper using a nonparametric modeling technique based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) model. Initially, the basic structure of this data modeling technique is presented and the main aspects regarding the development of a neuro-fuzzy model for MR dampers are addressed. Then, an ANFIS modeling technique is developed to obtain a non-parametric model for the MR damper. Finally, a comparison between the numerical and experimental results will be presented to validate the selected modeling technique.

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