System identification of hammerstein model a quarter car passive suspension systems using Multilayer Perceptron Neural Networks (MPNN)
Recently, Some Researchers Have Focused On The Applications System Identification. In This Paper, A Hammerstein Model Of A Quarter Car Passive Suspension System Is Identified Using Multilayer Perceptron Neural Networks. Input And Output Data Are Acquired By Driving A Car On A Special Road Event. Th...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit UTM Press
2005
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/1446/1/JTDIS43D7.pdf http://eprints.utm.my/id/eprint/1446/ http://dx.doi.org/10.11113/jt.v43.779 |
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| Summary: | Recently, Some Researchers Have Focused On The Applications System Identification. In This Paper, A Hammerstein Model Of A Quarter Car Passive Suspension System Is Identified Using Multilayer Perceptron Neural Networks. Input And Output Data Are Acquired By Driving A Car On A Special Road Event. The Networks Structure Is Based On System Model. The Network Learning Algorithm Is Based On Fisher’s Scoring Method. Fisher Information Is Given As A Weighted Covariance Matrix Of Inputs And Outputs Of The Network Hidden Layer. Unitwise, Fisher’s Scoring Method Reduces To The Algorithm In Which Each Unit Estimates Its Own Weights By A Weighted Least Square Method. The Results Show That The Minimum Mean Square Error (Mse) Value Of The Training Process Was Found With A Short Record. |
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