Modeling of magnetorheological damper using back propagation neural network

Ubaidillah; Gigih Priyandoko; Muhammad Nizam; Iwan Yahya

doi:10.4028/www.scientific.net/AMR.896.396

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Modeling of magnetorheological damper using back propagation neural network

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Ubaidillah, Gigih Priyandoko, Muhammad Nizam, Iwan Yahya

2014 Advanced Materials Research Vol. 896 Conference paper Cited by 7

Abstract

This paper presents a new approach to model magnetorheological (MR) dampers for semi-active suspension systems. The neural network method using back-propagation learning algorithm real is proposed. The experimental data collected from suspension test machine consist in time histories of current, displacement, velocity and force measured both for constant and variable current. The model parameters are determined using a set of experimental measurements corresponding to different current constant values. It has been shown that the damper response can be satisfactorily predicted with this model. © (2014) Trans Tech Publications, Switzerland.

Affiliations

Mechanical Engineering Department, Universitas Sebelas Maret (UNS), Kentingan Surakarta 57126, Jl. Ir. Sutami 36 A, Indonesia; Electrical Engineering Department, Universitas Widyagama Malang, Malang 65142, Kampus III: Jl. Taman Borobudur Indah No. 3, Indonesia; Department of Physics, Universitas Sebelas Maret, Kentingan Surakarta 57126, Jl. Ir. Sutami 36 A, Indonesia

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