@inproceedings{eec8a122ec2441fbb3b170eaa6d8b075,
title = "Adaptive dynamic programming and optimal stabilization for linear systems with time-varying uncertainty",
abstract = "This paper focuses on the optimal control of continuous-time linear time-varying uncertain systems with completely unknown internal dynamics and proposes a novel approach which leads to an optimal controller with guaranteed stability. A model-free algorithm of adaptive dynamic programming is employed to deal with the uncertainty of system parameters, yielding an optimal feedback controller for the system subject to a predefined cost. Then the stability of the system in time-varying uncertain situation which may undergo parameter changes or jumps is analyzed from the perspective of finite-time stability. On the basis of these results, a switching control strategy is presented to ensure the stability of the time-varying uncertain system with desired optimality properties in the long run. The effectiveness of the strategy is verified by simulations on a DC torque motor servo system.",
author = "Meng Zhang and Gan, \{Ming Gang\} and Jie Chen and Jiang, \{Zhong Ping\}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 11th Asian Control Conference, ASCC 2017 ; Conference date: 17-12-2017 Through 20-12-2017",
year = "2018",
month = feb,
day = "7",
doi = "10.1109/ASCC.2017.8287346",
language = "English",
series = "2017 Asian Control Conference, ASCC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1228--1233",
booktitle = "2017 Asian Control Conference, ASCC 2017",
address = "United States",
}