Vehicle lane keeping of adaptive PID control with BP neural network self-tuning

G. Zhenhai, Z. Bo
{"title":"Vehicle lane keeping of adaptive PID control with BP neural network self-tuning","authors":"G. Zhenhai, Z. Bo","doi":"10.1109/IVS.2005.1505082","DOIUrl":null,"url":null,"abstract":"According to the nonlinear and parameter time-varying characteristics of vehicle lateral dynamics, a novel algorithm of vehicle lateral adaptive PID control with BP neural network was proposed, using the approximate ability to any nonlinear function of the neural network. The results of the simulation in different velocities and lane curvature conditions show that the algorithm can effectively control vehicle to keep and track the pre-given trajectory and the good robustness and adaptability for the changing of velocity and path curvature is also shown.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2005.1505082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

According to the nonlinear and parameter time-varying characteristics of vehicle lateral dynamics, a novel algorithm of vehicle lateral adaptive PID control with BP neural network was proposed, using the approximate ability to any nonlinear function of the neural network. The results of the simulation in different velocities and lane curvature conditions show that the algorithm can effectively control vehicle to keep and track the pre-given trajectory and the good robustness and adaptability for the changing of velocity and path curvature is also shown.
基于BP神经网络自整定的车辆车道保持自适应PID控制
针对车辆横向动力学的非线性和参数时变特性,利用BP神经网络对任意非线性函数的逼近能力,提出了一种基于BP神经网络的车辆横向自适应PID控制算法。在不同速度和曲率条件下的仿真结果表明,该算法能有效地控制车辆保持和跟踪预定轨迹,对速度和路径曲率的变化具有良好的鲁棒性和适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信