摘要
为了提高模型预测控制(model predictive control,MPC)方法在高速无人驾驶汽车横向跟踪中的有效稳定控制,建立考虑横摆、侧滑和曲率等因素的高速车辆动力学模型,提出基于三次贝塞尔曲线的连续自适应分段拟合法以获取道路曲率,然后设计考虑车辆滑移稳定性约束、道路环境约束和轮胎纵横向耦合力约束,以车辆高速跟踪过程中的航向偏差、横向偏差以及滑移率等二次型最优为目标进行求解的MPC控制器。仿真案例基于MPC方法,搭建CarSim/SimuLink联合仿真模型,研究高附着路面恒定高速和低附着路面变速2种仿真工况。研究结果表明:车辆在恒定高速工况下以不同的车速在不同曲率的道路行驶时横向跟踪误差在0.6 m以内,优化的前轮转向角最大值为0.1 rad,横摆角速度-横向速度相平面也在包络线之内,车辆在大曲率路径跟踪时,平均横向跟踪误差0.2219 m,平均横摆角速度为0.1808 rad/s,较不考虑道路曲率/滑移稳定性约束的跟踪效果显著提升;低附着路面小曲率/大曲率路径变速工况下,车辆考虑轮胎耦合力的前轮转向角约束较未考虑时的横向跟踪误差显著减小(其中低附着路面小曲率路径工况的减幅为56.14%),横摆角速度-横向速度相平面范围也显著减小。所提出的方法能够在不同曲率及路面附着系数的地形下克服滑移、道路环境和轮胎纵横向耦合力约束,具有良好的横向跟踪精度且横摆稳定性较好。
In order to improve the effective stability control of the model predictive control(MPC)method in the lateral tracking of high-speed unmanned vehicles,a high-speed vehicle dynamics model considering yaw,sideslip and curvature was established.An adaptive piecewise fitting method based on cubic Bézier curve was proposed to obtain the road curvature.Then,a new MPC controller was designed with the objective of the quadratic optimization of the heading deviation,lateral deviation and slip rate,which considered the vehicle slip stability constraints,the road environment constraints and the coupling force of the tire constraints.Based on the MPC method,a CarSim Simulink co-simulation model was built in the simulation case.Two simulation conditions of constant high-speed on high adhesion road surface and variable speed on low adhesion road surface were simulated.The results show that under the condition of constant high speed,the lateral tracking error of the vehicle at different speeds in different road curvature is within0.6 m,the maximum optimized front wheel steering angle is 0.1 rad,and the phase plane of yaw rate and lateral velocity is also within the envelope.When the vehicle is tracking at constant speed in the large curvature path,the average lateral tracking error is 0.2219 m,and the average yaw rate is0.1808 rad·s-1,which is significantly improved,compared with the tracking effect without considering the constraint of road curvature/slip stability.Also the lateral tracking error of the front wheel steering angle constraint under the condition of low adhesion road with small curvature/large curvature path variable speed is significantly reduced,compared with that without considering the tire coupling force(the reduction is 56.14%under the condition of low adhesion road with small curvature path).The phase plane range of yaw rate and lateral velocity is also significantly reduced.In a word,the results show that the proposed method can overcome the constraints of slip,road environment and coupling force of the tire under different terrain curvature and road adhesion coefficient,and has good lateral tracking accuracy and yaw stability.4 tabs,31 figs,26 refs.
作者
刘平
刘自斌
杨明亮
巫超辉
LIU Ping;LIU Zi-bin;YANG Ming-liang;WU Chao-hui(School of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,Sichuan,China;Engineering Research Center of Advanced Drive Energy Saving Technology,Ministry ofEducation,Southwest Jiaotong University,Chengdu 610031,Sichuan,China)
出处
《长安大学学报（自然科学版）》
CAS
CSCD
北大核心
2023年第2期120-134,共15页
Journal of Chang’an University(Natural Science Edition)
基金
四川省科技厅重点研发项目(2020YFG0130)。
关键词
汽车工程
横向跟踪
模型预测控制
高速无人驾驶汽车
连续自适应分段拟合法
三次贝塞尔曲线
道路曲率
automobile engineering
lateral tracking
model predictive control(MPC)
high-speed unmanned vehicle
continuous adaptive piecewise fitting method
cubic Bézier curve
road curvature
作者简介
刘平(1969-),男,四川成都人,副教授,工学博士,E-mail:pingliu@swjtu.edu.cn。
