@inproceedings{7a2810d9b1c6480681faf8758bb6f50f,
title = "Model predictive control for UGV trajectory tracking based on dynamic model",
abstract = "In this paper, a simplified dynamic vehicle model is established to accurately describe the dynamics of Unmanned Ground Vehicle (UGV) in trajectory tracking, while meeting the real-Time computing requirement. And a modified model predictive control (MPC) algorithm with soft constraint for UGV trajectory tracking is proposed to improve the tracking stability and rapidity. The optimal control problem at each sampling time is converted into a quadratic program (QP), which has mature solutions. To verify the trajectory tracking capabilities, the proposed MPC controller is compared with a PD controller under different longitudinal velocities. The simulation results demonstrate that the MPC controller can effectively reduce the tracking error and ensure the vehicle's traveling smoothness.",
keywords = "Dynamic Model, Model Predictive Control, Soft Constraint, Trajectory Tracking, Unmanned Ground Vehicle",
author = "Wang Meiling and Wang Zhen and Yang Yi and Fu Mengyin",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016 ; Conference date: 01-08-2016 Through 03-08-2016",
year = "2017",
month = jan,
day = "24",
doi = "10.1109/ICInfA.2016.7832087",
language = "English",
series = "2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1676--1681",
booktitle = "2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016",
address = "United States",
}
