Model-Predictive-Control-based Simultaneous Trajectory Tracking and Speed Control for Intelligent Vehicles

被引:2
|
作者
Zhuang, Hanyang [1 ,2 ]
Hu, Yikai [3 ,4 ,5 ]
Wang, Chunxiang [3 ,4 ,5 ]
Yang, Ming [3 ,4 ,5 ]
机构
[1] Shanghai Jiao Tong Univ, Shanghai Jiao Tong Univ Joint Inst, Univ Michigan, Shanghai 200240, Peoples R China
[2] Guangxi Univ Sci & Technol, Guangxi Key Lab Automobile Components & Vehicle T, Liuzhou 545006, Peoples R China
[3] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
[4] Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
[5] Shanghai Engn Res Ctr Intelligent Control & Manag, Shanghai 200240, Peoples R China
来源
2021 27TH INTERNATIONAL CONFERENCE ON MECHATRONICS AND MACHINE VISION IN PRACTICE (M2VIP) | 2021年
基金
中国国家自然科学基金;
关键词
DESIGN;
D O I
10.1109/M2VIP49856.2021.9665044
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Trajectory tracking and speed control for intelligent vehicles are put forward higher requirements on accuracy by the high traffic density scenario. A standard Model Predictive Control (MPC) algorithm focuses on the trajectory tracking but ignores the speed control. This paper proposes a simultaneous trajectory tracking and speed control algorithm based on MPC approach to address fine control in both space and time dimensions for intelligent vehicles. A threefold cost function including lateral and longitudinal speed as well as comfort has been proposed to improve the control algorithm. The simulations and comparisons demonstrate that the proposed method has a better tracking and speed control performance than the existing method.
引用
收藏
页数:5
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