Application of neural networks in real time identification of dynamic structural response and prediction of road friction coefficient μ from steady state automobile response
- Delivery
- Available on this site
- Format
- Price
- Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880
- Publication code
- 9501744
- Paper/Info type
- AVEC
No.9438817
- Pages
- 527-532(Total 6 p)
- Date of publication
- Oct 1994
- Publisher
- Others, Unknown
- Language
- English
- Event
- AVEC '92
Detailed Information
| Author(E) | 1) Chinmoy PAL, 2) Ichiro HAGIWARA, 3) Hideki INOUE, 4) Shin MORISHITA |
|---|---|
| Affiliation(E) | 1) Nissan Motor Co., Ltd./Japan, 2) Nissan Motor Co., Ltd./Japan, 3) Nissan Motor Co., Ltd./Japan, 4) Yokohama National University/Japan |
| Abstract(J) | 適切な動的システムの線形モデルを用いた車両コントロール技術は多くあるが,より高度化された車両の増加にもかかわらず,いくつかの研究は,道路摩擦係数とサスペンション特性の種類による非線形応答予測を適用しているが,道路摩擦係数予想の適用,非線形応答認識技術をベースとしたニューラルネットワークの適用について理論的に考察した. Translation |
| Abstract(E) | Most of the existing control techniques applied on automobile field is based on the linear model of the relevant dynamic system. However, in spite of the increasing demand of more sophisticated vehicles, few researches are directed in understanding and predicting the non-linear response caused by non-predictable operating conditions such as the variation of suspension characteristics due to wear and tear, the frictional coefficient of road and etc. In this paper, we applied the neural-network based identification technique to predict the structural response of a non-linear system and applied it to forecast the frictional coefficient of the road. Numerical results indicate promising future applications on actual on-board control system likely to be implemented in the near future. |
