@inproceedings{0bff1eb5b8294e8d888a08955404a49c,
title = "Distributed model predictive control of linear systems with unmeasurable states and uncertain parameters",
abstract = "Distributed model predictive control (DMPC) is widely used in complex industrial process control. The theoretical researches of DMPC have got more and more attention because of its good performances, such as the ability of dealing with all kinds of constraints effectively, high flexibility and fault tolerance. In this paper, the linear systems with uncertain parameters and unmeasurable states are confirmed by generalized polynomial chaos expansion method. Then the DMPC algorithm is realized by using the state observers to estimate states.",
keywords = "DMPC, Deterministic system, Stable, State estimator, Uncertain parameter, Unmeasurable state",
author = "Wei Zhao and Baihai Zhang and Senchun Chai and Lingguo Cui and Fenxi Yao",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017 ; Conference date: 19-05-2017 Through 21-05-2017",
year = "2017",
month = jun,
day = "30",
doi = "10.1109/YAC.2017.7967540",
language = "English",
series = "Proceedings - 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "916--921",
booktitle = "Proceedings - 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017",
address = "United States",
}