Research on Intelligent Vehicle Trajectory Planning and Control Based on an Improved Terminal Sliding Mode

被引:5
|
作者
Li, Aijuan [1 ]
Niu, Chuanhu [1 ]
Li, Shunming [2 ]
Huang, Xin [3 ]
Xu, Chuanyan [1 ]
Liu, Gang [4 ]
机构
[1] Shandong Jiaotong Univ, Sch Automot Engn, Jinan 250357, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Coll Energy & Power Engn, Nanjing 210016, Peoples R China
[3] Shandong Jiaotong Univ, Sch Informat Sci & Elect Engn, Jinan 250357, Peoples R China
[4] Shandong Jiaotong Univ, Off Acad Affairs, Jinan 250357, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 05期
基金
中国国家自然科学基金;
关键词
intelligent vehicle; target bias strategy; separation axis theorem; improved RRT algorithm; improved terminal sliding mode control; TRACKING CONTROL; RRT-ASTERISK;
D O I
10.3390/app12052446
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Aiming at precisely tracking an intelligent vehicle on a desired trajectory, this paper proposes an intelligent vehicle trajectory planning and control strategy based on an improved terminal sliding mold. Firstly, the traditional RRT algorithm is improved by using the target bias strategy and the separation axis theorem to improve the algorithm search efficiency. Secondly, an improved terminal sliding mode controller is designed. The controller comprehensively considers the lateral error and heading error of the tracking control, and the stability of the control system is proven by the Lyapunov function. Finally, the performance of the designed controller is verified by the Matlab-Carsim HIL simulation platform. The test results of the Matlab-Carsim HIL simulation platform show that, compared with the general terminal sliding mode controller, the improved terminal sliding mode controller designed in this paper has higher control accuracy and better robustness.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Sliding Mode Control for Trajectory Tracking of Intelligent Vehicle
    Yang, Jun
    Ma, Rong
    Zhang, Yanrong
    Zhao, Chengzhi
    Fug, Weiping
    2011 INTERNATIONAL CONFERENCE ON COMPUTERS, COMMUNICATIONS, CONTROL AND AUTOMATION (CCCA 2011), VOL II, 2010, : 521 - 524
  • [2] Sliding Mode Control for Trajectory Tracking of Intelligent Vehicle
    Yang, Jun
    Ma, Rong
    Zhang, Yanrong
    Zhao, Chengzhi
    2012 INTERNATIONAL CONFERENCE ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING (ICMPBE2012), 2012, 33 : 1160 - 1167
  • [3] Study on Intelligent Vehicle Trajectory Planning and Tracking Control Based on Improved APF and MPC
    Chen, Qiping
    Yu, Binghao
    Min, Shilong
    Gan, Lu
    Luo, Chagen
    Zeng, Dequan
    Hu, Yiming
    Liu, Qin
    INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, 2024, : 715 - 728
  • [4] Intelligent vehicle trajectory tracking with an adaptive robust nonsingular fast terminal sliding mode control in complex scenarios
    Gao, Min
    Li, Jing
    Hu, Taihong
    Luo, Jin
    Feng, Baidong
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [5] Dynamic trajectory planning and tracking control for lane change of intelligent vehicle based on trajectory preview
    Nie Z.-G.
    Wang W.-Q.
    Zhao W.-Q.
    Huang Z.
    Zong C.-F.
    Zhao, Wei-Qiang (zwqjlu@163.com), 1600, Chang'an University (20): : 147 - 160
  • [6] Trajectory Tracking Control of Intelligent Electric Vehicles Based on the Adaptive Spiral Sliding Mode
    Nie, Yanxin
    Zhang, Minglu
    Zhang, Xiaojun
    APPLIED SCIENCES-BASEL, 2021, 11 (24):
  • [7] Recursive terminal sliding mode control for hypersonic flight vehicle with sliding mode disturbance observer
    Wang, Jianmin
    Wu, Yunjie
    Dong, Xiaomeng
    NONLINEAR DYNAMICS, 2015, 81 (03) : 1489 - 1510
  • [8] Longitudinal control of an intelligent vehicle using particle swarm optimization based sliding mode control
    Thanok, Somphong
    Parnichkun, Manukid
    ADVANCED ROBOTICS, 2015, 29 (08) : 525 - 543
  • [9] Intelligent vehicle path following control based on sliding mode active disturbance rejection control
    Wu Y.
    Wang L.-F.
    Li F.
    Kongzhi yu Juece/Control and Decision, 2019, 34 (10): : 2150 - 2156
  • [10] Research on the motion trajectory optimization method based on the improved genetic algorithm for an intelligent vehicle
    Li, Aijuan
    Zhao, Wanzhong
    Li, Shunming
    Qiu, Xuyun
    Wang, Xibo
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2016, 230 (13) : 1729 - 1740