@inproceedings{c4e137d5185740bc8977ddd9d628a0f0,
title = "A Trajectory Tracking Method Using Convex Optimization",
abstract = "To improve the efficiency of the existing convex optimization-based trajectory tracking method, and address the issue that the existing trajectory tracking methods are very sensitive to the deviations of axial states, a new trajectory tracking method using convex optimization in conjunction with a modified receding horizon control strategy is developed in this paper. The trajectory tracking is implemented in each segment of trajectory in successive using the convex optimization method. To ensure online guidance, the optimal control problem of trajectory tracking in each segment is transformed into an exact convex optimization, which can be solved in only one iteration. Meanwhile, to address the deviation of axial states, a time re-planning method is proposed to ensure the accuracy and robustness of trajectory tracking. Simulation results show that the proposed methods can track the reference trajectory with high accuracy and robustness with respect to various disturbances.",
keywords = "Axial states deviation, Convex optimization, Receding horizon control, Trajectory tracking",
author = "Ze An and Xiong, {Fen Fen} and Chao Li",
note = "Publisher Copyright: {\textcopyright} 2020 Technical Committee on Control Theory, Chinese Association of Automation.; 39th Chinese Control Conference, CCC 2020 ; Conference date: 27-07-2020 Through 29-07-2020",
year = "2020",
month = jul,
doi = "10.23919/CCC50068.2020.9188469",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "3281--3287",
editor = "Jun Fu and Jian Sun",
booktitle = "Proceedings of the 39th Chinese Control Conference, CCC 2020",
address = "United States",
}