Intelligent system identification for an axis of car passive suspension system using real data
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 networ...
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| Main Authors: | , , , |
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| 格式: | Book Section |
| 出版: |
Institute of Electrical and Electronics Engineers
2009
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| 主題: | |
| 在線閱讀: | http://eprints.utm.my/id/eprint/12895/ http://dx.doi.org/10.1109/ISMA.2009.5164792 |
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| 總結: | 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 identifcation contructed 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. |
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