摘要
针对智能汽车纵横向耦合非线性导致的控制系统模型复杂度高以及轮胎侧偏刚度不确定性影响控制效果的问题,提出了一种基于轮胎侧偏刚度估计的纵横向整体反馈线性化控制方法。首先,建立智能汽车纵横向耦合动力学模型和轨迹跟踪偏差模型;其次,对车辆模型的线性化条件进行了判定,利用李雅普诺夫稳定性分析方法设计了可以保证系统稳定和跟踪误差渐近收敛的虚拟控制律;然后,对轮胎侧偏刚度进行了实时估计;最后,通过基于CarSim/Simulink的高速紧急双移线仿真实验,验证了本文提出的方法可使智能汽车在纵横向耦合工况行驶时具有良好的轨迹跟踪性能和稳定性。
Aiming at the problems of high model complexity of control system and the tire cornering stiffness uncertainty affecting the control effect caused by longitudinal and lateral coupling nonlinearity of intelligent vehicle,a longitudinal and lateral integrated feedback linearization control method based on Lyapunov stability theory and tire cornering stiffness estimation is proposed.Firstly,the longitudinal and lateral coupling model and the trajectory tracking error model was established.Secondly,the exact linearization condition of the system was determined,and the virtual control law was designed to ensure the stability of the system and the asymptotic convergence of the tracking error by using the Lyapunov stability analysis method.Then,the real-time estimation of the tire cornering stiffness was carried out.The simulation results based on CarSim/Simulink demonstrate that the proposed method can make the intelligent vehicle keep good trajectory tracking performance and stability in longitudinal and lateral coupling conditions.
作者
高松
王玉琼
王玉海
徐艺
周英超
王鹏伟
GAO Song;WANG Yu-qiong;WANG Yu-hai;XU Yi;ZHOU Ying-chao;WANG Peng-wei(School of Transportation and Vehicle Engineering,Shandong University of Technology,Zibo 255000,China;State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun 130022,China;Qingdao Automotive Research Institute,Jilin University,Qingdao 266043,China)
出处
《吉林大学学报(工学版)》
EI
CAS
CSCD
北大核心
2023年第3期735-745,共11页
Journal of Jilin University:Engineering and Technology Edition
基金
山东省重大科技创新工程项目(2019JZZY010911)
国家自然科学基金项目(51905320,52102465)
山东省自然科学基金面上项目(ZR2022MF230)。
关键词
车辆工程
反馈线性化
虚拟控制律
纵横向耦合
轮胎侧偏刚度估计
vehicle engineering
feedback linearization
virtual control law
longitudinal and lateral coupling
tire cornering stiffness estimation