Path tracking control strategy for off-road 4WS4WD vehicle based on robust model predictive control

被引:11
|
作者
Tan, Qifan [1 ]
Qiu, Cheng [1 ]
Huang, Jing [1 ]
Yin, Yue [2 ]
Zhang, Xinyu [2 ]
Liu, Huaping [3 ]
机构
[1] Beijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing 100044, Peoples R China
[2] Tsinghua Univ, Sch Vehicle & Mobil, Beijing 100084, Peoples R China
[3] Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
基金
中国博士后科学基金;
关键词
Mobile robot; 4WS4WD vehicle; Path tracking; Model Predictive Control; Robustness; STABILITY;
D O I
10.1016/j.robot.2022.104267
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the increasing requirements for vehicle adaptability and maneuverability in various road environ-ments, four-wheel-steering four-wheel-drive (4WS4WD) vehicles have attracted wider attention. This paper presents a robust model predictive control-based strategy for the path tracking of 4WS4WD vehicles considering external disturbances. The strategy combines model predictive control (MPC) and control allocation under an upper-lower structure. The main objective of the present work is to improve the robustness and stability of path tracking by developing an MPC algorithm in the upper layer. The controller design considers general disturbances caused by allocation errors and sudden disturbances caused by an outer force in the offset model. Based on the offset model, a robust MPC control law is obtained by converting the robustness constraints into a linear matrix inequality. The control law is mathematically demonstrated to be stable in multidisturbed conditions via the Lyapunov stability theorem. Through comparison with a similar control algorithm of path tracking and applying it on different uneven ground conditions, the proposed robust algorithm is found to effectively overcome disturbances on the system.(c) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页数:12
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