@inproceedings{b8349733780743e6b0b20f3990de1045,
title = "An online single-network adaptive algorithm for continuous-time nonlinear optimal control",
abstract = "In this paper, we propose an online adaptive neural-algorithm to solve the CT nonlinear optimal control problems. Compared to the existing methods, which adopt the architecture with two neural networks (NNs) for actor-critic implementations, only one NN for critic is used to implement the algorithm, simplifying the structure of the computation model. Moreover, we also provide a generalized learning rule for updating the NN weights, which covers the existing critic update rules as special cases. The theoretical and numerical results are given under the required persistent excitation condition to verify and analyze stability and performance of the proposed method.",
keywords = "Adaptive control, actor-critic, approximate dynamic programming, nonlinear control, optimal control",
author = "Lee, {Jae Young} and Park, {Jin Bae} and Choi, {Yoon Ho} and Lee, {Keun Uk}",
year = "2013",
doi = "10.1109/ICCAS.2013.6704205",
language = "English",
isbn = "9788993215052",
series = "International Conference on Control, Automation and Systems",
pages = "1687--1690",
booktitle = "ICCAS 2013 - 2013 13th International Conference on Control, Automation and Systems",
note = "2013 13th International Conference on Control, Automation and Systems, ICCAS 2013 ; Conference date: 20-10-2013 Through 23-10-2013",
}