Robust controller design for trajectory tracking of autonomous vehicle

被引:1
作者
Xueyun L. [1 ]
Shuang L. [2 ]
Ju Z. [1 ]
机构
[1] School of Vehicle Engineering, Hubei University of Automotive Technology, Shiyan
[2] School of College of Mechanical Engineering, Sichuan University, Chengdu
关键词
Autonomous vehicle; Dual-loop weighted control; Fault tolerance; Lane changing; Lateral displacement; Robust controller; Stability; Trajectory tracking; Weighting coefficient; Yaw rate;
D O I
10.1504/IJVP.2020.111406
中图分类号
学科分类号
摘要
In order to improve the stability and fault tolerance of the control system of the autonomous vehicle in the middle and low speed lane changing, a dual loop weighted trajectory tracking robust control system is designed. Firstly, the lateral displacement transfer function and yaw angle transfer function are derived by combining the mathematical model of trajectory planning and vehicle motion, and the proportion integral differential (PID) control parameters are calculated by mathematical derivation and transfer function reduction. Then, the influence of weighting coefficient on system stability and its determination method are studied by simulation. The results show that the dual-loop weighted control is feasible and effective, and it could provide a good fault tolerance, good control ability, good tracking effect, and small lateral displacement error and yaw angular velocity error for lane changing conditions in the medium and low speed. Copyright © 2020 Inderscience Enterprises Ltd.
引用
收藏
页码:381 / 398
页数:17
相关论文
共 30 条
[1]  
Ashraf M.A., Takeda J-i., Torisu R., Neural network based steering controller for vehicle navigation on sloping land, Engineering in Agriculture Environment & Food, 3, 3, pp. 100-104, (2010)
[2]  
Aslam J., Shi-Yin Q., Fuzzy sliding mode control algorithm for a four-wheel skid steer vehicle, Journal of Mechanical Science and Technology, 28, 8, pp. 3301-3310, (2014)
[3]  
Dazhi H., Yuanliang Z., Fuzzy control of intelligent tracing vehicles, Information Technology Journal, 12, 10, pp. 2016-2022, (2013)
[4]  
Guerrero J., Torres J., Creuze V., Chemori A., Campos E., Saturation based nonlinear PID control for underwater vehicles: design, stability analysis and experiments, Mechatronics, 61, pp. 96-105, (2019)
[5]  
Guo J.M., Tian X.J., Liu Q., Real-time trajectory tracking of wheel mobile robot based on fuzzy neural networks, Journal of Wuhan University of Technology, 31, 8, pp. 128-132, (2009)
[6]  
Haijian B., Jianfeng S., Liyang W., Zhongxiang F., Accelerated Lane-changing trajectory planning of automated vehicles with vehicle-to-vehicle collaboration, Journal of Advanced Transportation, 3, pp. 1-11, (2017)
[7]  
Han G., Fu W., Wang W., Wu Z., The lateral tracking control for the intelligent vehicle based on adaptive PID neural network, SENSORS, 17, 6, (2017)
[8]  
Han X., Zhang X., Du Y., Cheng G., Design of autonomous vehicle controller based on BP-PID, IOP Conference Series: Earth and Environmental Science, 234, 1, (2019)
[9]  
Jiang L., Wu Z., Liding mode control for intelligent vehicle trajectory tracking based on reaching law, Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 49, 3, pp. 381-386, (2018)
[10]  
Kanako K., Tadatsugi O., Masakazu A., Study on optimal tuning of PID autopilot for autonomous surface vehicle, IFAC PapersOnLine, 52, 21, pp. 335-340, (2019)