@inproceedings{b08f10586ae142a2842f1cfa847d6807,
title = "Modeling CO2 Recovery for Optimal Dynamic Operations",
abstract = "The development of amine scrubbing processes for coal and natural gas-fired power plants is essential to reduce CO2 emissions. The design of tailor-made dynamic models to predict CO2 capture in amine scrubbing processes is fundamental for optimal control operations. This paper presents the use of SIMPCA, a subspace system identification technique used to develop a dynamic empirical model for an LQG controller with integral action. Such a controller is made to attain optimal operating conditions for a CO2 capture pilot plant. Reference signals are used in conjunction with the controller integral action to bring few process outputs towards their set-points. The results illustrate the importance of reliable model prediction in order to provide desirable closed loop response and appropriate CO2 emission reduction. {\textcopyright} 2011 IEEE.",
author = "Ricardo DUNIA and ROCHELLE, {Gary T.} and QIN, {S. Joe}",
year = "2011",
month = dec,
doi = "10.1109/CDC.2011.6160356",
language = "English",
isbn = "9781612848006",
series = "Proceedings of the IEEE Conference on Decision and Control",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "6475--6480",
booktitle = "2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011",
note = "50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 ; Conference date: 12-12-2011 Through 15-12-2011",
}