Intelligent system identification for an axis of car passive suspension system using real data

Author

Hanafi, Dirman ; Rahmat, Mohd Fuaad Bin ; Ahmad, Zainal Abidin Bin ; bin Mohd Zaid, Amran

Author_Institution

Dept. of Mechatron. & Robotic Engineeering, Univ. Tun Hussein Onn Malaysia, Parit Raja, Malaysia

fYear

2009

fDate

23-26 March 2009

Firstpage

1

Lastpage

7

Abstract

This paper presents an intelligent system identification using multilayer perceptron neural network algorithm for an axis car passive suspension model. Nonlinear autoregressive with exogenous input (NARX) model were assumed for the system in order to determine the multilayer perceptron neural network structure. The intelligent system identification constructed for NARX model used real input output data acquired by driving a car on a special road event. The results show that the method proposed is suitable for modeling a quarter car passive suspension systems.

Keywords

automated highways; automobiles; multilayer perceptrons; traffic engineering computing; axis car passive suspension model; car passive suspension system; intelligent system identification; multilayer perceptron neural network algorithm; nonlinear autoregressive with exogenous input model; Electronic mail; Intelligent networks; Intelligent robots; Intelligent systems; Multi-layer neural network; Multilayer perceptrons; Neural networks; Parameter estimation; Roads; System identification; Intelligent system identification; Multilayer perceptron; NARX model; real input output data;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics and its Applications, 2009. ISMA '09. 6th International Symposium on

Conference_Location

Sharjah

Print_ISBN

978-1-4244-3480-0

Electronic_ISBN

978-1-4244-3481-7

Type

conf

DOI

10.1109/ISMA.2009.5164792

Filename

5164792