An individualized robust stability control strategy for active front steering vehicles

Han Zhang, Yuan Li, Weimei Quan, Wanzhong Zhao
{"title":"An individualized robust stability control strategy for active front steering vehicles","authors":"Han Zhang, Yuan Li, Weimei Quan, Wanzhong Zhao","doi":"10.1177/09544070231218355","DOIUrl":null,"url":null,"abstract":"To improve the vehicle stability and driver steering performance, this paper presents an individualized yaw stability control strategy based on H∞ robust control for active front steering (AFS) vehicles. A driver-vehicle system, including a driver steering model and a vehicle dynamics model with AFS, is formed. To analyze the steering characteristics of different drivers, a set of driving data of 36 drivers is collected, and the driver’s characteristics parameters are identified by using the particle swarm optimization (PSO) algorithm. A general evaluation function considering the trajectory tracking performance, vehicle stability, driver workloads, and driver’s characteristics parameters are established to evaluate the comprehensive steering performance. To accomplish the personalized control of vehicle yaw stability, an individualized H∞ robust yaw stability controller is presented by adjusting the gain of the weighting function according to the general evaluation of each driver. Driver-in-the-loop experiment is conducted based on the Matlab/Simulink-CarSim®-Prescan co-simulation platform, and the results demonstrates that the proposed control strategy can provide driver with individualized driving assistance while improving the overall driving performance and reducing the driver’s workloads.","PeriodicalId":509770,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/09544070231218355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

To improve the vehicle stability and driver steering performance, this paper presents an individualized yaw stability control strategy based on H∞ robust control for active front steering (AFS) vehicles. A driver-vehicle system, including a driver steering model and a vehicle dynamics model with AFS, is formed. To analyze the steering characteristics of different drivers, a set of driving data of 36 drivers is collected, and the driver’s characteristics parameters are identified by using the particle swarm optimization (PSO) algorithm. A general evaluation function considering the trajectory tracking performance, vehicle stability, driver workloads, and driver’s characteristics parameters are established to evaluate the comprehensive steering performance. To accomplish the personalized control of vehicle yaw stability, an individualized H∞ robust yaw stability controller is presented by adjusting the gain of the weighting function according to the general evaluation of each driver. Driver-in-the-loop experiment is conducted based on the Matlab/Simulink-CarSim®-Prescan co-simulation platform, and the results demonstrates that the proposed control strategy can provide driver with individualized driving assistance while improving the overall driving performance and reducing the driver’s workloads.
主动前转向车辆的个性化鲁棒稳定性控制策略
为了提高车辆稳定性和驾驶员转向性能,本文提出了一种基于 H∞ 鲁棒控制的主动前转向(AFS)车辆个性化偏航稳定性控制策略。本文建立了一个驾驶员-车辆系统,包括驾驶员转向模型和带有 AFS 的车辆动力学模型。为了分析不同驾驶员的转向特性,收集了一组 36 名驾驶员的驾驶数据,并利用粒子群优化(PSO)算法确定了驾驶员的特性参数。建立了考虑轨迹跟踪性能、车辆稳定性、驾驶员工作量和驾驶员特征参数的一般评价函数,以评价综合转向性能。为了实现车辆偏航稳定性的个性化控制,根据每个驾驶员的总体评价,通过调整加权函数的增益,提出了个性化的 H∞ 鲁棒偏航稳定性控制器。基于 Matlab/Simulink-CarSim®-Prescan 协同仿真平台进行了驾驶员在环实验,结果表明所提出的控制策略可以为驾驶员提供个性化的驾驶辅助,同时提高整体驾驶性能并降低驾驶员的工作负荷。
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