@inproceedings{e8818963ddec4bda88f467b2d6f2a6e6,
title = "Data-driven nonlinear adaptive optimal control of connected vehicles",
abstract = "This paper studies the cooperative adaptive cruise control (CACC) problem of connected vehicles with unknown nonlinear dynamics. Different from the existing literature on CACC, a data-driven optimal control policy is developed by global adaptive dynamic programming (GADP). Interestingly, the developed control policy achieves global stabilization of the nonlinear vehicular platoon system in the absence of the a priori knowledge of system dynamics. Numerical simulation results are presented to validate the effectiveness of the developed approach.",
keywords = "Connected and autonomous vehicles, Cooperative adaptive cruise control, Global adaptive dynamic programming, Nonlinear optimal control",
author = "Weinan Gao and Jiang, {Zhong Ping}",
year = "2017",
doi = "10.1007/978-3-319-70136-3_13",
language = "English (US)",
isbn = "9783319701356",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "122--129",
editor = "Derong Liu and Shengli Xie and Dongbin Zhao and Yuanqing Li and El-Alfy, {El-Sayed M.}",
booktitle = "Neural Information Processing - 24th International Conference, ICONIP 2017, Proceedings",
note = "24th International Conference on Neural Information Processing, ICONIP 2017 ; Conference date: 14-11-2017 Through 18-11-2017",
}