@inproceedings{781160071b8041388d1b0d4449375b00,
title = "Adaptive and optimal output feedback control of linear systems: An adaptive dynamic programming approach",
abstract = "This paper proposes a computational adaptive optimal output feedback control method for continuous-time linear systems. By periodic sampling, we use measurable input/output data to reconstruct the unmeasurable state, and then utilize adaptive dynamic programming (ADP) technique to iteratively solve the discrete-time algebraic Riccati equation. An exploration noise is introduced for online learning purpose without compromising accuracy of the proposed iterative algorithm. The stability and the optimality of the sampled-data system in close-loop with the proposed control policy are also analyzed. The feasibility of the output feedback ADP scheme is validated by simulation on a third-order linear system.",
keywords = "Approximate/adaptive dynamic programming(ADP), Optimal control, Output feedback, Sampled-data systems",
author = "Weinan Gao and Yu Jiang and Jiang, {Zhong Ping} and Tianyou Chai",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 11th World Congress on Intelligent Control and Automation, WCICA 2014 ; Conference date: 29-06-2014 Through 04-07-2014",
year = "2015",
month = mar,
day = "2",
doi = "10.1109/WCICA.2014.7053043",
language = "English (US)",
series = "Proceedings of the World Congress on Intelligent Control and Automation (WCICA)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "March",
pages = "2085--2090",
booktitle = "Proceeding of the 11th World Congress on Intelligent Control and Automation, WCICA 2014",
edition = "March",
}