全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于粒子滤波算法的汽车状态估计技术

Keywords: 汽车动力学,状态估计,粒子滤波算法,虚拟试验

Full-Text   Cite this paper   Add to My Lib

Abstract:

将粒子滤波(particlefilter,PF)算法应用到汽车的状态估计之中,建立了包含定常统计特性噪声和非线性轮胎的汽车动力学模型,根据汽车非线性状态转移函数完成对粒子的预测,基于当前时刻的量测值实现对预测粒子权重的评估,最后通过重采样完成对汽车关键状态量估计。将PF估计器与常见的EKF、UKF估计器进行了比较分析,基于ADAMS/Car的虚拟试验和实车试验验证了PF在汽车状态估计中的可行性。

References

[1]  赵又群;林棻,基于UKF算法的汽车状态估计,中国机械工程,2010(5).
[2]  林棻;赵又群,基于双重扩展自适应卡尔曼滤波的汽车状态和参数估计,中国机械工程,2009(6).
[3]  M. C. BEST ;T. J. GORDON ;P. J. DIXON,An Extended Adaptive Kalman Filter for Real-time State Estimation of vehicle Handling Dynamics,Vehicle System Dynamics?,2000, 34(1).
[4]  Wenzel T A;Burnham K J;Blundell M V,Kalman filter as a virtual sensor:applied to automotive stability systems,Transactions of the Institute of Measurement and Control,2007(2).
[5]  Wan E A;Nelson A T,Kalman filtering and neural networks,New York:John Wiley and Sons,Inc,2001.
[6]  M. Sanjeev Arulampalam ;Simon Maskell ;Neil Gordon ;Tim Clapp,A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking,IEEE Transactions on Signal Processing?,2002, 50(2).
[7]  郭孔辉,汽车操纵动力学,长春:吉林科学技术出版社,1991.
[8]  林棻;赵又群.汽车侧偏角估计方法比较[J].南京理工大学学报(自然科学版),2009(01)
[9]  Pierre D M;Arnaud D;Ajay J,Sequential Monte Carlo samplers,Journal of the Royal Statistical Society,Series B:Statistical Methodology,2006(3).
[10]  Dan Crisan ;Arnaud Doucet,A Survey of Convergence Results on Particle Filtering Methods for Practitioners,IEEE Transactions on Signal Processing?,2002, 50(3).
[11]  PAUL J.TH. VENHOVENS ;KARL NAAB,Vehicle Dynamics Estimation Using Kalman Filters,Vehicle System Dynamics?,1999, 32(2/3).

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133