Optimal design of Neural Networks for estimation of tyre/road friction

被引：14
|
作者：
Pasterkamp, WR [1 ]
Pacejka, HB [1 ]
机构：
[1] Delft Univ Technol, Vehicle Res Lab, NL-2628 CD Delft, Netherlands
来源：
VEHICLE SYSTEM DYNAMICS | 1998年 / 29卷
关键词：
D O I：
10.1080/00423119808969567
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
In previous publications [1,2] it was shown that the tyre can be used as a sensor to estimate the tyre-to-road friction coefficient. In the estimation procedure, Neural Networks were used to describe the tyre and wheel suspension behaviour. In this paper the problem of selecting the optimal network architecture for the estimation problem is addressed. A general network architecture is discussed from which a particular network is derived by optimization using a Genetic Algorithm. Results on experimental data are shown.
引用
收藏
页码：312 / 321
页数：10
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