Modelling magneto-rheological damper using radial basis function neural network

This is a study on modeling the MR damper using RBF. MR damper can be simplify as a damper that using MR fluids. MR fluid contains magnetic particles which will react to current flow when power is supplied. The viscosity of the fluid depends on the current flow. The stiffness of the damper depends o...

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Main Author: Mohd Fikri, Arifin
Format: Undergraduates Project Papers
Language:English
Published: 2013
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/8381/
http://umpir.ump.edu.my/id/eprint/8381/1/CD8028_%40_48.pdf
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author Mohd Fikri, Arifin
author_facet Mohd Fikri, Arifin
author_sort Mohd Fikri, Arifin
building UMP Institutional Repository
collection Online Access
description This is a study on modeling the MR damper using RBF. MR damper can be simplify as a damper that using MR fluids. MR fluid contains magnetic particles which will react to current flow when power is supplied. The viscosity of the fluid depends on the current flow. The stiffness of the damper depends on the fluids. This modeling is to achieve the similarity of the results of the experiment using proper machine and apparatus and by using MATLAB software. The data that are obtained from the experiment are used in the MATLAB software to generate graphs. The RBF equations are used in the m-file to get the similarity as the graph from experiment. Comparisons between the graphs are decided by inspection and the most accurate, by using the RMSE graph. The input in m-file is adjusted again and again to get the smallest RMSE as possible
first_indexed 2025-11-15T01:34:16Z
format Undergraduates Project Papers
id ump-8381
institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T01:34:16Z
publishDate 2013
recordtype eprints
repository_type Digital Repository
spelling ump-83812021-07-08T04:17:30Z http://umpir.ump.edu.my/id/eprint/8381/ Modelling magneto-rheological damper using radial basis function neural network Mohd Fikri, Arifin TL Motor vehicles. Aeronautics. Astronautics This is a study on modeling the MR damper using RBF. MR damper can be simplify as a damper that using MR fluids. MR fluid contains magnetic particles which will react to current flow when power is supplied. The viscosity of the fluid depends on the current flow. The stiffness of the damper depends on the fluids. This modeling is to achieve the similarity of the results of the experiment using proper machine and apparatus and by using MATLAB software. The data that are obtained from the experiment are used in the MATLAB software to generate graphs. The RBF equations are used in the m-file to get the similarity as the graph from experiment. Comparisons between the graphs are decided by inspection and the most accurate, by using the RMSE graph. The input in m-file is adjusted again and again to get the smallest RMSE as possible 2013-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/8381/1/CD8028_%40_48.pdf Mohd Fikri, Arifin (2013) Modelling magneto-rheological damper using radial basis function neural network. Faculty of Mechanical Engineering , Universiti Malaysia Pahang.
spellingShingle TL Motor vehicles. Aeronautics. Astronautics
Mohd Fikri, Arifin
Modelling magneto-rheological damper using radial basis function neural network
title Modelling magneto-rheological damper using radial basis function neural network
title_full Modelling magneto-rheological damper using radial basis function neural network
title_fullStr Modelling magneto-rheological damper using radial basis function neural network
title_full_unstemmed Modelling magneto-rheological damper using radial basis function neural network
title_short Modelling magneto-rheological damper using radial basis function neural network
title_sort modelling magneto-rheological damper using radial basis function neural network
topic TL Motor vehicles. Aeronautics. Astronautics
url http://umpir.ump.edu.my/id/eprint/8381/
http://umpir.ump.edu.my/id/eprint/8381/1/CD8028_%40_48.pdf