Trajectory Tracking Control of Autonomous Vehicle with Double Layer Controller

Jiarui Song; Gang Tao; Zheng Wu; Haotian Dong; Shaobin Wu; Jianwei Gong

doi:10.1109/CAC53003.2021.9727558

Trajectory Tracking Control of Autonomous Vehicle with Double Layer Controller

Jiarui Song, Gang Tao, Zheng Wu, Haotian Dong, Shaobin Wu, Jianwei Gong^*

^*Corresponding author for this work

School of Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Aiming at improving the yaw stability of unmanned ground vehicles during high-speed steering, a double layer control architecture based on feedback linearization and model predictive control is proposed. The upper controller uses the model predictive control algorithm and the lower controller uses the feedback linearization method. This architecture makes full use of the performance advantages of the two controllers and improves the accuracy of the controller model and the path tracking performance while ensuring the real-time performance of the calculation. Finally, the effectiveness of this control framework is verified by the joint simulation of MATLAB/Simulink and CarSim, which proves that the performance of this controller is higher than that of the single-layer dynamic MPC controller.

Original language	English
Title of host publication	Proceeding - 2021 China Automation Congress, CAC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3507-3512
Number of pages	6
ISBN (Electronic)	9781665426473
DOIs	https://doi.org/10.1109/CAC53003.2021.9727558
Publication status	Published - 2021
Event	2021 China Automation Congress, CAC 2021 - Beijing, China Duration: 22 Oct 2021 → 24 Oct 2021

Publication series

Name	Proceeding - 2021 China Automation Congress, CAC 2021

Conference

Conference	2021 China Automation Congress, CAC 2021
Country/Territory	China
City	Beijing
Period	22/10/21 → 24/10/21

Keywords

MATLAB/Simulink CarSim co-simulation
Unmanned ground vehicle
double layer controller
feedback linearization
model predictive control

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10.1109/CAC53003.2021.9727558

Cite this

Song, J., Tao, G., Wu, Z., Dong, H., Wu, S., & Gong, J. (2021). Trajectory Tracking Control of Autonomous Vehicle with Double Layer Controller. In Proceeding - 2021 China Automation Congress, CAC 2021 (pp. 3507-3512). (Proceeding - 2021 China Automation Congress, CAC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAC53003.2021.9727558

@inproceedings{250ae95655854ebe9186cf5b57216c85,

title = "Trajectory Tracking Control of Autonomous Vehicle with Double Layer Controller",

abstract = "Aiming at improving the yaw stability of unmanned ground vehicles during high-speed steering, a double layer control architecture based on feedback linearization and model predictive control is proposed. The upper controller uses the model predictive control algorithm and the lower controller uses the feedback linearization method. This architecture makes full use of the performance advantages of the two controllers and improves the accuracy of the controller model and the path tracking performance while ensuring the real-time performance of the calculation. Finally, the effectiveness of this control framework is verified by the joint simulation of MATLAB/Simulink and CarSim, which proves that the performance of this controller is higher than that of the single-layer dynamic MPC controller.",

keywords = "MATLAB/Simulink CarSim co-simulation, Unmanned ground vehicle, double layer controller, feedback linearization, model predictive control",

author = "Jiarui Song and Gang Tao and Zheng Wu and Haotian Dong and Shaobin Wu and Jianwei Gong",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 China Automation Congress, CAC 2021 ; Conference date: 22-10-2021 Through 24-10-2021",

year = "2021",

doi = "10.1109/CAC53003.2021.9727558",

language = "English",

series = "Proceeding - 2021 China Automation Congress, CAC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3507--3512",

booktitle = "Proceeding - 2021 China Automation Congress, CAC 2021",

address = "United States",

}

Song, J, Tao, G, Wu, Z, Dong, H, Wu, S & Gong, J 2021, Trajectory Tracking Control of Autonomous Vehicle with Double Layer Controller. in Proceeding - 2021 China Automation Congress, CAC 2021. Proceeding - 2021 China Automation Congress, CAC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 3507-3512, 2021 China Automation Congress, CAC 2021, Beijing, China, 22/10/21. https://doi.org/10.1109/CAC53003.2021.9727558

Trajectory Tracking Control of Autonomous Vehicle with Double Layer Controller. / Song, Jiarui; Tao, Gang; Wu, Zheng et al.
Proceeding - 2021 China Automation Congress, CAC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 3507-3512 (Proceeding - 2021 China Automation Congress, CAC 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Trajectory Tracking Control of Autonomous Vehicle with Double Layer Controller

AU - Song, Jiarui

AU - Tao, Gang

AU - Wu, Zheng

AU - Dong, Haotian

AU - Wu, Shaobin

AU - Gong, Jianwei

PY - 2021

Y1 - 2021

N2 - Aiming at improving the yaw stability of unmanned ground vehicles during high-speed steering, a double layer control architecture based on feedback linearization and model predictive control is proposed. The upper controller uses the model predictive control algorithm and the lower controller uses the feedback linearization method. This architecture makes full use of the performance advantages of the two controllers and improves the accuracy of the controller model and the path tracking performance while ensuring the real-time performance of the calculation. Finally, the effectiveness of this control framework is verified by the joint simulation of MATLAB/Simulink and CarSim, which proves that the performance of this controller is higher than that of the single-layer dynamic MPC controller.

AB - Aiming at improving the yaw stability of unmanned ground vehicles during high-speed steering, a double layer control architecture based on feedback linearization and model predictive control is proposed. The upper controller uses the model predictive control algorithm and the lower controller uses the feedback linearization method. This architecture makes full use of the performance advantages of the two controllers and improves the accuracy of the controller model and the path tracking performance while ensuring the real-time performance of the calculation. Finally, the effectiveness of this control framework is verified by the joint simulation of MATLAB/Simulink and CarSim, which proves that the performance of this controller is higher than that of the single-layer dynamic MPC controller.

KW - MATLAB/Simulink CarSim co-simulation

KW - Unmanned ground vehicle

KW - double layer controller

KW - feedback linearization

KW - model predictive control

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U2 - 10.1109/CAC53003.2021.9727558

DO - 10.1109/CAC53003.2021.9727558

M3 - Conference contribution

AN - SCOPUS:85128080669

T3 - Proceeding - 2021 China Automation Congress, CAC 2021

SP - 3507

EP - 3512

BT - Proceeding - 2021 China Automation Congress, CAC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 China Automation Congress, CAC 2021

Y2 - 22 October 2021 through 24 October 2021

ER -

Trajectory Tracking Control of Autonomous Vehicle with Double Layer Controller

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