@inproceedings{5a9d36dc4b5c44c689ebfd8f0f9aa982,
title = "Nonlinear Dynamics based Trajectory Tracking Robust Control of Unmanned Ground Vehicle",
abstract = "This paper investigates the issue of unmanned ground vehicles (UGVs) trajectory tracking. A model predictive control and nonlinear dynamics-based robust control (MPC-NDRC) framework is suggested for UGV to improve trajectory tracking performance. The MPC-NDRC framework is divided into two phases. Building a predictive model controller is the first step in preventing the issue of poor real-time performance brought on by online computing complex models. The creation of a robust nonlinear dynamics-based controller is the second step in ensuring the performance of trajectory tracking and controller model accuracy. Additionally, by designing the system's poles with a stability margin, the system's robust stability is ensured. The Lyapunov theorem establishes the sufficient condition for closed-loop system stability. The MATLAB-Carsim platform's simulation results show the proposed MPC-NDRC framework considerably improves trajectory tracking performance.",
keywords = "MATLAB/Simulink-Carsim, Unmanned ground vehicles, model predictive control, robust control, trajectory tracking",
author = "Jiarui Song and Gang Tao and Zheng Zang and Derun Li and Xingjie Fu and Jianwei Gong",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022 ; Conference date: 28-10-2022 Through 30-10-2022",
year = "2022",
doi = "10.1109/CVCI56766.2022.9964599",
language = "English",
series = "2022 6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022",
address = "United States",
}