机械科学与技术2012，Vol.31Issue(10)：1592-1595,4.
基于神经网络的方程式赛车操纵逆动力学研究
Exploring Inverse Dynamics for Handling Formula Racing Car with Neural Network
倪俊 1吴志成 1陈思忠1
作者信息
- 1. 北京理工大学机械与车辆学院,北京100081
- 折叠
摘要
Abstract
We aim to build the nonlinear mapping relationship between the angular velocity and the steering angle of a certain formula racing car. Its virtual prototype model was built by using the simulation software ADAMS. tak- ing into consideration the nonlinear factors such as tire and damping and their aerodynamics characteristics. Under the steering angle step input condition, the nonlinear mapping relationship between the angular velocity and the steering angle was built by using the radial basis function (RBF) neural network. The input identification results show that the above method is not only feasible but also highly accurate.关键词
方程式赛车/非线性映射/识别/ADAMS/径向基函数网络Key words
formula racing car/non-linear mapping/prototype model/inverse dynamics/radial basis function (RBF) neural network分类
交通工程引用本文复制引用
倪俊,吴志成,陈思忠..基于神经网络的方程式赛车操纵逆动力学研究[J].机械科学与技术,2012,31(10):1592-1595,4.
