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Trajectory tracking control algorithm of lane changing for intelligent vehicle based on model prediction and angle compensation |
LI Shengqin, XING Jiaqi |
College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin, Heilongjiang 150040, China |
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Abstract To improve the accuracy of path tracking and the vehicle handling stability in the process of automatic driving tracking, a trajectory tracking control method based on model predictive control principle and angle compensation was proposed. The overall control structure was divided into two layers, and the upper layer was the trajectory tracking control layer. According to the obtained road information and the driving state of the vehicle, the front wheel steering control input was determined by the model predictive control algorithm. In the lower layer, the sliding mode control theory was used to design the angle compensator, and the yaw rate deviation of the vehicle was taken as the control target to achieve accurate tracking. The results show that compared with the single-point preview strategy, the trajectory tracking control strategy based on model prediction and angle compensation can better control the vehicle to achieve trajectory tracking, and the peak values of yaw rate and sideslip angle are significantly reduced with better stability.
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Received: 03 April 2022
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[1] |
张亮修,张铁柱,吴光强.考虑误差校正的智能车辆路径跟踪鲁棒预测控制 [J].西安交通大学学报,2020,54(3):20-27.
|
|
ZHANG L X, ZHANG T Z, WU G Q. Robust predictive control for intelligent vehicle path tracking considering error feedback correction [J]. Journal of Xi′an Jiaotong University, 2020,54 (3):20-27. (in Chinese)
|
[2] |
URMSON C, RAGUSA C, RAY D, et al. A robust approach to high-speed navigation for unrehearsed desert terrain [J]. Journal of Field Robotics, 2006, 23(8):467-508.
|
[3] |
AL-MAYYAHI A, WANG W, BIRCH P. Path tracking of autonomous ground vehicle based on fractional order PID controller optimized by PSO [C]∥2015 IEEE 13th International Symposium on Applied Machine Intelligence and Informatics. Piscataway,USA:IEEE,2015:109-114.
|
[4] |
SUBROTO R K, WANG C Z, LIAN K L. Four-wheel independent driver electric vehicle stability control using novel adaptive sliding mode control [J]. IEEE Transactions on Industry Applications, 2020, 56(5):5995-6006.
|
[5] |
吴晟博,曹理想.无人驾驶车辆轨迹跟踪控制研究 [J].汽车实用技术,2020(1):51-53.
|
|
WU S B, CAO L X. Research on trajectory tracking control of driverless vehicles [J]. Automobile Applied Technology, 2020 (1): 51-53. (in Chinese)
|
[6] |
MATA S, ZUBIZARRETA A, PINTO C. Robust tube-based model predictive control for lateral path tracking [J]. IEEE Transactions on Intelligent Vehicles, 2019, 4(4):569-577.
|
[7] |
WANG H Y, LIU B, PING X Y, et al. Path tracking control for autonomous vehicles based on an improved MPC [J]. IEEE Access, 2019, 7:161064-161073.
|
[8] |
龚建伟, 刘凯, 齐建勇. 无人驾驶车辆模型预测控制 [M].北京: 北京理工大学出版社, 2020.
|
[9] |
FALCONE P, BORRELLI F, ASGARI J, et al. Predictive active steering control for autonomous vehicle systems [J]. IEEE Transactions on Control Systems Technology, 2007,15(3):566-580.
|
[10] |
WANG Z J, ZHA J Q, WANG J M. Flatness-based model predictive control for autonomous vehicle trajectory tracking [C]∥2019 Intelligent Transportation Systems Conference.Piscataway,USA:IEEE,2019:4146-4151.
|
[11] |
HOU Q S, ZHANG Y A, ZHAO S, et al. Tracking control of intelligent vehicle lane change based on RLMPC [J]. E3S Web of Conferences, DOI:10.1051/e3sconf/202123304019.
|
[12] |
李胜琴,张明瑞.基于双五次多项式的智能汽车换道路径规划研究 [J].南京信息工程大学学报(自然科学版),DOI:10.13878/j.cnki.jnuist.20230614001.
|
|
LI S Q, ZHANG M R. Research on lane change path planning intelligent vehicle based on double quintic poly-nomial [J]. Journal of Nanjing University of Information Science and Technology (Natural Science Edition),DOI:10.13878/j.cnki.jnuist.20230614001. (in Chinese)
|
|
|
|