基于Frenet坐标系和控制延时补偿的智能车辆路径跟踪
Path Tracking for Intelligent Vehicles Based on Frenet Coordinates and Delayed Control
查看参考文献22篇
|
文摘
|
对智能车辆路径跟踪问题中存在的控制延时问题进行研究。前轮转角表述为纯滞后和1阶惯性延时的串联结构模型,通过使用Matlab/Simulink建立转向控制延时模型,并对实车采集的转向控制数据进行分析,完成延时模型的参数辨识;基于V-REP和ROS搭建仿真测试平台,根据延时模型的辨识结果模拟转向响应特性,实现与实车转向特性等效的控制延时效果;基于Frenet坐标系和运动学、动力学模型构建不考虑控制延时和考虑控制延时的模型预测控制(MPC)路径跟踪控制器,使得控制器可以直接扩展到多车编队行驶场景;在V-REP仿真环境中设置以5 m/s、10 m/s、20 m/s车速采集的变曲率参考路径,先针对无延时系统考察不考虑控制延时的MPC路径跟踪控制器,获得了平均跟踪误差低于0.22 m的控制效果,验证了不考虑控制延时的MPC控制器在处理无延时车辆系统路径跟踪问题的跟踪性能,再针对大延时车辆系统对比测试两种MPC控制器。试验结果表明:考虑控制延时的MPC控制器相比不考虑控制延时的MPC控制器取得了较大的效果提升,特别是在最大跟踪误差和航向误差指标上表现优异,平均跟踪误差降低了83.7%,最大跟踪误差降低了74.4%;对于高延时系统,低速工况下考虑延时的运动学MPC表现更好,而高速工况动力学MPC表现出了更加稳定的跟踪性能,20 m/s延时试验中仅考虑控制延时的动力学MPC控制器安全地跑完了全程。 |
|
其他语种文摘
|
The path tracking problem for intelligent vehicle with delayed control inputs is studied. The cramping angle is expressed as a series structure model with pure lag and first-order inertial delay, and a steering control delay model is established using Matlab/Simulink. The collected steering control data of an actual vehicle is analyzed for parameter identification of the proposed delay model.The equivalent delay performance in simulation environment based on V-REP and ROS is implemented. The model predictive control (MPC)-based path tracking controllers without or with considering delay control are designed based on Frenet coordinates, and the kinematic and dynamics models, which can also be used for marching vehicle formation. A curvature-variant reference paths collected at 5, 10 and 20 m/s are set in V-REP simulation environment. Three curvature-variant reference paths are presented. For the MPC path tracking controller without delay modeling, the average tracking error is less than 0.22 m for a vehicle platform without control delay. The MPC controllers with and without delay modeling are tested to compare their tracking performances for the vehicle system with long control delay. Simulated results indicate that the average and maximum tracking errors of MPC controller with delay modeling are 83.7% and 74.4% less than those of MPC controller without delay modeling when they are used on a vehicle with delayed control inputs. The kinematics-based MPC controller performs better at low speed, whereas the dynamics-based MPC controller performs better at high speed. Only dynamics-based MPC controller with delay modeling completed the whole test safely at 20 m/s on the vehicle with delayed control. |
|
来源
|
兵工学报
,2019,40(11):2336-2351 【核心库】
|
|
DOI
|
10.3969/j.issn.1000-1093.2019.11.019
|
|
关键词
|
智能车辆
;
路径跟踪
;
延时建模
;
模型预测控制
|
|
地址
|
北京理工大学机械与车辆学院, 北京, 100081
|
|
语种
|
中文 |
|
文献类型
|
研究性论文 |
|
ISSN
|
1000-1093 |
|
学科
|
公路运输 |
|
基金
|
国家部委预研项目
|
|
文献收藏号
|
CSCD:6628686
|
参考文献 共
22
共2页
|
|
1.
陈慧岩.
无人驾驶汽车概论,2014
|
CSCD被引
32
次
|
|
|
|
|
2.
陈慧岩. 军用地面无人机动平台技术发展综述.
兵工学报,2014,35(10):1696-1706
|
CSCD被引
43
次
|
|
|
|
|
3.
Kritayakirana K. Autonomous vehicle control at the limits of handling.
International Journal of Vehicle Autonomous Systems,2012,10(4):271-296
|
CSCD被引
8
次
|
|
|
|
|
4.
Snider J M.
Automatic steering methods for autonomous automobile path tracking,2009:1-78
|
CSCD被引
1
次
|
|
|
|
|
5.
孙银健.
基于模型预测控制的无人驾驶车辆轨迹跟踪控制算法研究,2015
|
CSCD被引
24
次
|
|
|
|
|
6.
Amer N H. Modelling and control strategies in path tracking control for autonomous ground vehicles: a review of state of the art and challenges.
Journal of Intelligent & Robotic Systems,2017,86(2):225-254
|
CSCD被引
16
次
|
|
|
|
|
7.
Brown M. Safe driving envelopes for path tracking in autonomous vehicles.
Control Engineering Practice,2017,61:307-316
|
CSCD被引
29
次
|
|
|
|
|
8.
Rasekhipour Y. A potential field-based model predictive path-planning controller for autonomous road vehicles.
IEEE Transactions on Intelligent Transportation Systems,2017,18(5):1255-1267
|
CSCD被引
61
次
|
|
|
|
|
9.
Ai B. Stability and performance analysis of time-delayed actuator control systems.
Journal of Dynamic Systems, Measurement, and Control,2016,138(5):051005
|
CSCD被引
2
次
|
|
|
|
|
10.
Nikulin V. Regression-based supervised learning of autosteering of a road car featuring a delayed steering response.
International Journal of Data Science and Analytics,2018:1-15
|
CSCD被引
1
次
|
|
|
|
|
11.
Jalali M. Handling delays in yaw rate control of electric vehicles using model predictive control with experimental verification.
Journal of Dynamic Systems, Measurement, and Control,2017,139(12):121001
|
CSCD被引
1
次
|
|
|
|
|
12.
Nahidi A. A study on actuator delay compensation using predictive control technique with experimental verification.
Mechatronics,2019,57:140-149
|
CSCD被引
2
次
|
|
|
|
|
13.
张玉.
自动驾驶车辆混合运动规划研究,2018
|
CSCD被引
4
次
|
|
|
|
|
14.
Dineen S.
Multivariate calculus and geometry,2001
|
CSCD被引
1
次
|
|
|
|
|
15.
Werling M. Optimal trajectory generation for dynamic street scenarios in a Frenet frame.
Proceedings of IEEE International Conference on Robotics and Automation,2010:987-993
|
CSCD被引
16
次
|
|
|
|
|
16.
Saska M. Predictive control and stabilization of nonholonomic formations with integrated spline-path planning.
Robotics and Autonomous Systems,2016,75:379-397
|
CSCD被引
4
次
|
|
|
|
|
17.
Barfoot T D. Motion planning for formations of mobile robots.
Robotics and Autonomous Systems,2004,46(2):65-78
|
CSCD被引
8
次
|
|
|
|
|
18.
Zhu M. A model predictive speed tracking control approach for autonomous ground vehicles.
Mechanical Systems and Signal Processing,2017,87:138-152
|
CSCD被引
23
次
|
|
|
|
|
19.
Quigley M. ROS: an open-source robot operating system.
Proceedings of ICRA Workshop on Open Source Software,2009
|
CSCD被引
5
次
|
|
|
|
|
20.
Freese M. Virtual robot experimentation platform V-REP: a versatile 3d robot simulator.
Proceedings of International Conference on Simulation, Modeling, and Programming for Autonomous Robots,2010:51-62
|
CSCD被引
1
次
|
|
|
|
|
了解气象卫星更多信息，请访问