基于学习型模型预测控制的智能车辆路径跟踪控制

doi:10.19562/j.chinasae.qcgc.2024.10.008

Abstract

Abstract:

Path tracking control is a key technology for intelligent vehicles. However， the existing vehicle tracking control methods mostly rely on more accurate vehicle control models， while actual vehicle control systems mostly have modeling errors， parameter perturbations and external disturbances， which significantly affect path tracking control accuracy. In this paper， a learning path tracking control method for intelligent vehicles considering unmodeled dynamics of vehicles is proposed. Firstly， a nominal model of the vehicle is established and a linear prediction model is used to approximate the compensation for the unmodeled dynamics of the vehicle to improve the accuracy of the vehicle model. Then， learning and updating of the parameters of the unmodeled dynamics are realized based on the principle of Extended Kalman Filtering. Next， learning Model Predictive Controller （LMPC） considering the unmodeled dynamics of the system is established. Finally， the effectiveness of the proposed method in improving the path tracking accuracy is verified by designing a joint simulation test with Carsim and Matlab/Simulink for multiple operating conditions and multiple groups.

Key words: intelligent vehicle, path tracking control, unmodeled dynamics, parameter learning, learning model predictive control

Hongmao Qin,Shu Jiang,Tiantian Zhang,Heping Xie,Yougang Bian,Yang Li. Path Tracking Control of Intelligent Vehicle Based on Learning Model Predictive Control[J].Automotive Engineering, 2024, 46(10): 1804-1815.

Figures/Tables 8

学习型模型预测控制算法流程
1：初始化后验估计值 $x ? k$ ，误差协方差矩阵 $p k$ ，过程噪声协方差矩阵 $Q k$ ，测量噪声协方差矩阵 $R k$ ，系统噪声边界 $d x a u g, k$ 和权重系数 Q 、 R
2：建立车辆标称模型
3：对系统未建模动态进行线性化建模，得到预言模型，并与标称模型整合得到学习型预测模型
4：构建包含系统状态量和待学习参数的增广非线性系统
5：For k=1 To final waypoint
6：更新车辆当前状态 $x = Y φ β ω T$
7：利用EKF将非线性系统线性化，并进行系统状态优化、未建模动态矩阵 $F k$ 、 $H k$ 、 $g k$ 参数更新学习
8：得到包含已知未建模动态参数的系统学习型预测模型
9：寻找未来P步的系统参考路径跟踪点
10：建立LMPC的优化问题
11：二次型优化问题转化与求解
12：将得到的最优控制序列中的第1个元素作用于系统，等待下一个控制周期到来
13：End

参数	数值	单位
车辆轴距	2.91	m
质心到前轴距离	1.015	m
质心到后轴距离	1.895	m
簧上质量	1 270	kg
质心转动惯量	1 536.7	$k g . m 2$
前轮侧偏刚度	-61 126	N/rad
后轮侧偏刚度	-51 163	N/rad
LMPC采样步长	0.1	s
LMPC预测步数	10
控制周期	0.02	s
过程噪声协方差矩阵	0.01 I
测量噪声协方差矩阵	0.04 I
系统噪声边界	［-0.01，0.01］

References 33

1	采国顺，刘昊吉，冯吉伟，等. 智能汽车的运动规划与控制研究综述［J］.汽车安全与节能学报， 2021， 12（3）： 279-297.
	CAI G S， LIU H J， FENG J W， et al. Review on the research of motion planning and control for intelligent vehicles［J］. J Automotive Safety and Energy， 2021， 12（3）： 279-297.
2	TENG S， HU X， DENG P， et al. Motion planning for autonomous driving： the state of the art and future perspectives［J］. IEEE Transactions on Intelligent Vehicles， 2023， 8（6）： 3692-3711.
3	金立生，谢宪毅，司法，等. 考虑驾驶人特性的智能驾驶路径跟踪算法［J］.汽车工程， 2021， 43（4）： 553-561.
	JIN L S， XIE X Y， SI F， et al. Intelligent driving path tracking algorithm considering driver characteristics［J］. Automotive Engineering， 2021， 43（4）： 553-561.
4	胡杰，钟鑫凯，陈瑞楠，等. 基于模糊LQR的智能汽车路径跟踪控制［J］.汽车工程， 2022， 44（1）： 17-25，43.
	HU J， ZHONG X K， CHEN R N， et al. Path tracking control of intelligent vehicles based on fuzzy LQR［J］. Automotive Engineering， 2022， 44（1）： 17-25，43.
5	AMER N H， HUDHA K， ZAMZURI H， et al. Adaptive modified stanley controller with fuzzy supervisory system for trajectory tracking of an autonomous armoured vehicle［J］. Robotics and Autonomous Systems， 2018， 105： 94-111.
6	XU S， PENG H. Design， analysis， and experiments of preview path tracking control for autonomous vehicles［J］. IEEE Transactions on Intelligent Transportation Systems， 2020， 21（1）： 48-58.
7	MARINO R， SCALZI S， NETTO M. Nested PID steering control for lane keeping in autonomous vehicles［J］. Control Engineering Practice， 2011， 19（12）： 1459-1467.
8	WAN N， ZENG G， ZHANG C， et al. Multi-layer controller with state-constraint： vehicle lateral stability control based on fuzzy logic［J］. Proceedings of the Institution of Mechanical Engineers， Part D： Journal of Automobile Engineering， 2022， 236（1）： 155-167.
9	JIANG Y， XU X， ZHANG L. Heading tracking of 6WID/4WIS unmanned ground vehicles with variable wheelbase based on model free adaptive control［J］. Mechanical Systems and Signal Processing， 2021， 159： 107715.
10	FARAG W. Complex trajectory tracking using PID control for autonomous driving［J］. International Journal of Intelligent Transportation Systems Research， 2020， 18（2）： 356-366.
11	XIONG B， QU S. Intelligent vehicle's path tracking based on fuzzy control［J］. Journal of Transportation Systems Engineering and Information Technology， 2010， 10（2）： 70-75.
12	WANG Z， ZHOU X， WANG J. Extremum-seeking-based adaptive model-free control and its application to automated vehicle path tracking［J］. IEEE/ASME Transactions on Mechatronics， 2022， 27（5）： 3874-3884.
13	SNIDER J M. Automatic steering methods for autonomous automobile path tracking［J］. Robotics Institute， Pittsburgh， PA， Tech Rep CMU-RITR-09-08， 2009.
14	潘世举，李永乐，李子先，等. 基于改进纯跟踪的智能车路径跟随方法［J］.汽车工程， 2023， 45（1）： 1-8，19.
	PAN S J， LI Y L， LI Z X， et al. Path following method of intelligent vehicles based on improved pure tracking［J］. Automotive Engineering， 2023， 45（1）： 1-8，19.
15	BACHA S， SAADI R， AYAD M Y， et al. A review on vehicle modeling and control technics used for autonomous vehicle path following［C］.2017 International Conference on Green Energy Conversion Systems （GECS）. IEEE， 2017： 1-6.
16	YANG J， BAO H， MA N， et al. An algorithm of curved path tracking with prediction model for autonomous vehicle［C］.2017 13th International Conference on Computational Intelligence and Security （CIS）. IEEE， 2017： 405-408.
17	熊璐，杨兴，卓桂荣，等. 无人驾驶车辆的运动控制发展现状综述［J］.机械工程学报， 2020， 56（10）： 127-143.
	XIONG L， YANG X， ZHUO G R， et al. Review on motion control of autonomous vehicles［J］. Journal of Mechnical Engineering， 2020， 56（10）： 127-143.
18	QINPENG S， ZHONGHUA W， MENG L， et al. Path tracking control of wheeled mobile robot based on improved pure pursuit algorithm［C］.2019 Chinese Automation Congress （CAC）. IEEE， 2019： 4239-4244.
19	AHN J， SHIN S， KIM M， et al. Accurate path tracking by adjusting look-ahead point in pure pursuit method［J］. International Journal of Automotive Technology， 2021， 22： 119-129.
20	THRUN S， MONTEMERLO M， DAHLKAMP H， et al. Stanley： the robot that won the DARPA grand challenge［J］. Journal of field Robotics， 2006， 23（9）： 661-692.
21	ABDELMONIEM A， OSAMA A， ABDELAZIZ M， et al. A path-tracking algorithm using predictive Stanley lateral controller［J］. International Journal of Advanced Robotic Systems， 2020， 17（6）： 1729881420974852.
22	周卫琪，赵羿寒，刘擎超，等. 基于改进LQR的车辆路径跟踪横向控制策略［J］.华中科技大学学报（自然科学版）， 2024， 52（3）： 135-141.
	ZHOU W Q， ZHAO Y H， LIU Q C， et al. Lateral control strategy of vehicle path tracking based on improved LQR［J］. J. Huazhong Univ. of Sci. & Tech， 2024， 52（3）： 135-141.
23	FAN Z， CHEN H. Study on path following control method for automatic parking system based on LQR［J］. SAE International Journal of Passenger Cars-Electronic and Electrical Systems， 2016， 10（2016-01-1881）： 41-49.
24	陈亮，秦兆博，孔伟伟，等. 基于最优前轮侧偏力的智能汽车LQR横向控制［J］.清华大学学报（自然科学版）， 2021， 61（9）： 906-912.
	CHEN L， QING Z B， KONG W W， et al. Lateral control using LQR for intelligent vehicles based on the optimal front-tire lateral force［J］. J Tsinghua Univ （Sci & Technol）， 2021， 61（9）： 906-912.
25	LIU T， SHEN Y， WANG K. Path tracking control for autonomous truck with dual modular chassis［J］. Automotive Innovation， 2023， 6（4）： 558-570.
26	GENG K， LIU S. Robust path tracking control for autonomous vehicle based on a novel fault tolerant adaptive model predictive control algorithm［J］. Applied Sciences， 2020， 10（18）： 6249.
27	BIAN Y， DING J， HU M， et al. An advanced lane-keeping assistance system with switchable assistance modes［J］. IEEE Transactions on Intelligent Transportation Systems， 2020， 21（1）： 385-396.
28	余志生. 汽车理论［M］. 北京：机械工业出版社， 2009.
	YU Z S. Automobile theory［M］. Beijing： Machinery Industry Press， 2009.
29	DOGAN I， SHEN Z J M， ASWANI A. Regret analysis of learning-based MPC with partially-unknown cost function［J］. IEEE Transactions on Automatic Control， 2023： 1-8.
30	LJUNG L. Asymptotic behavior of the extended Kalman filter as a parameter estimator for linear systems［J］. IEEE Transactions on Automatic Control， 1979， 24（1）： 36-50.
31	边有钢，张田田，胡云卿，等. 一种自动驾驶车辆学习型路径跟踪预测控制方法： CN113306573B［P］. 2022-08-16.
	BIAN Y G， ZHANG T T， HU Y Q， et al. A learning path tracking predictive control method for automated vehicles： CN113306573B［P］. 2022-08-16.
32	王艺，蔡英凤，陈龙，等. 基于模型预测控制的智能网联汽车路径跟踪控制器设计［J］.机械工程学报， 2019， 55（8）： 136-144，153.
	WANG Y， CAI Y F， CHEN L， et al. Design of intelligent and connected vehicle path tracking controller based on model predictive control［J］. Journal of Mechnical Engineering， 2019， 55（8）： 136-144，153.
33	TONG Y， LI C， WANG G， et al. Integrated path-following and fault-tolerant control for four-wheel independent-driving electric vehicles［J］. Automotive Innovation， 2022， 5（3）： 311-323.

[1]	ZHOU Wei, ZHANG Cheng-Ning, LI Jun-Qiu. [J]. , 2016, 38(12): 1407 -1414 .
[2]	LI Huan, HUANG Ying, ZHANG Fu-Jun, ZHAO Yu, GE Yan-Wu. [J]. , 2016, 38(12): 1420 -1426 .
[3]	HAO Han, WANG Si-南, LI Xiao, LIU Zong-Wei, ZHAO Fu-Quan. [J]. , 2017, 39(1): 1 -8 .
[4]	ZONG Yi-Qi, GU Zheng-Qi, LUO Ze-Min, JIANG Cai-Mao, ZHANG Qi-Dong, YANG Zhen-Dong. [J]. , 2016, 38(12): 1427 -1433 .
[5]	XU Cheng-Shan, JIANG Fa-Chao, SONG Sen-Nan, TIAN Guang-Yu. [J]. , 2017, 39(1): 9 -14 .
[6]	SHEN Zhe, WANG Yi-Gang, YANG Zhi-Gang, LI Fang-Xu. [J]. , 2016, 38(12): 1440 -1445 .
[7]	ZHANG Yi-Bing, 吕Jian-Jun , YUAN Guang-Hui. [J]. , 2016, 38(12): 1467 -1470 .
[8]	KONG Xiang-Dong, ZHANG Zhen-Dong, XIE Nai-Liu, CHENG Qiang, YIN Cong-Bo. [J]. , 2016, 38(12): 1471 -1476 .
[9]	ZHANG Lei, ZHANG Jin-Qiu, LUO Tao, BI Zhan-Dong, YAO Jun. [J]. , 2016, 38(12): 1494 -1499 .
[10]	PENG Qian-Lei, GUI Liang-Jin, FAN Zi-Jie. [J]. , 2016, 38(12): 1500 -1507 .

车速/（km·h^-1）	MPC/m	LMPC/m	性能提升/%
72	0.074	0.044	40.54
54	0.031	0.021	32.26
36	0.014	0.007	50.00
18	0.005	0.002	60.00

车速/（km·h^-1）	MPC/m	LMPC/m	性能提升/%
54	0.035	0.014	60.00
36	0.018	0.009	50.00
18	0.005	0.002	60.00

[1]	Xianghao Meng,Ling Niu,Junqiang Xi,Danni Chen,Chao Lü. Risk Prediction of Heterogeneous Traffic Participants Based on Spatio-Temporal Graph Neural Networks [J]. Automotive Engineering, 2024, 46(9): 1537-1545.
[2]	Xiujian Yang,Yongrui Bai. Trajectory Planning for Intelligent Vehicle in Dynamic Unstructured Environment Based on the Graph Search and Optimization Methods [J]. Automotive Engineering, 2024, 46(9): 1564-1575.
[3]	Jing Zhao,Hao Liang,Tianxiao Xu,Yayue Xiao,Bowen Jiang. Research on Domain Specific Modeling Language for Intelligent Vehicle Cyber-Physical System [J]. Automotive Engineering, 2024, 46(8): 1370-1381.
[4]	Jialiang Zhu,Qiaobin Liu,Fan Yang,Lu Yang,Weihua Li. Two-Dimensional Collision Risk Prediction for Intelligent Vehicles Considering the Influence of Heterogeneous Vehicle Types [J]. Automotive Engineering, 2024, 46(8): 1414-1421.
[5]	Xiaolin Fan,Xudong Zhang,Yuan Zou,Xin Yin,Yingqun Liu. A Mapping and Planning Method Based on Simplified Visibility Graph [J]. Automotive Engineering, 2024, 46(7): 1249-1258.
[6]	Shuen Zhao,Sheng Wang,Yao Leng. Multi-objective Explicit Model Predictive Control for Intelligent Vehicle Trajectory Tracking [J]. Automotive Engineering, 2024, 46(5): 784-794.
[7]	Bing Zhu,Yinzi Huang,Jian Zhao,Peixing Zhang,Jingwei Xue. A Criticality Assessment Model for the Intelligent Vehicle Test Scenario Based on the Onboard Camera Images [J]. Automotive Engineering, 2024, 46(4): 557-563.
[8]	Ting Chikit,Yafei Wang,Yichen Zhang,Mingyu Wu,Yile Wang. Energy-Saving Planning Method for Autonomous Driving Mining Trucks Based on Composite Dynamic Sampling [J]. Automotive Engineering, 2024, 46(4): 588-595.
[9]	Zhong Zhang,Xiaojian Wu,Huihua Jiang,Chao Zhang,Yukang Wan. Model Predictive Anti-disturbance Control for Longitudinal Motion of Intelligent Vehicles Under Multi-source Disturbances [J]. Automotive Engineering, 2024, 46(10): 1816-1828.
[10]	Junhui Zhang,Xiaoman Guo,Yuxi Liu,Mingqiang Zheng,Yuhan Qian,Yuxuan Ding. Driver-Automation Shared Lane-Keeping Robust Control [J]. Automotive Engineering, 2024, 46(10): 1853-1862.
[11]	Jianping Hao,Yanzhao Su,Zhihua Zhong,Jin Huang. Service-Oriented Architecture and Service Scheduling Mechanism for Intelligent Vehicles [J]. Automotive Engineering, 2023, 45(9): 1563-1572.
[12]	Gaoshi Zhao,Long Chen,Yingfeng Cai,Yubo Lian,Hai Wang,Qingchao Liu,Chenglong Teng. Trajectory Prediction Technology Integrating Complex Network and Memory-Augmented Network [J]. Automotive Engineering, 2023, 45(9): 1608-1616.
[13]	Yougang Bian,Tiantian Zhang,Heping Xie,Hongmao Qin,Zeyu Yang. Anti-disturbance and Anti-corner-cutting Control for Collaborative Path Tracking of Vehicle Platoon [J]. Automotive Engineering, 2023, 45(8): 1320-1332.
[14]	Lin Hu,Gen Li,Fang Wang,Miao Lin,Ning Wu. Research on Test Scenarios of Passenger Cars and Two-Wheelers at Intersections Based on CIDAS Accident Data [J]. Automotive Engineering, 2023, 45(8): 1417-1427.
[15]	Qihui Hu,Yingfeng Cai,Hai Wang,Long Chen,Zhaozhi Dong,Qingchao Liu. Heterogeneous Multi-object Trajectory Prediction Method Based on Hierarchical Graph Attention [J]. Automotive Engineering, 2023, 45(8): 1448-1456.

Path Tracking Control of Intelligent Vehicle Based on Learning Model Predictive Control

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 33

Related Articles 15

Metrics

Comments

Recommended 10