0446538 20240111140906.420150818235959.9 84940945621 000370259201123 10.1109/ACC.2015.7170973 6 s. C cav_un_epca*0446537978-1-4799-8684-20743-16191671-1676Chicago, ILIEEE2015 Identification Model predictive control Building climate control cav_un_auth*0305702 Žáčeková E. CZ cav_un_auth*0281469 Pčolka M. CZ cav_un_auth*0318861 Tabaček J. CZ cav_un_auth*0318862 Těžký J. CZ cav_un_auth*0304632 Robinett R. US cav_un_auth*0101074 Teorie řízení Department of Control Theory TŘ TR Department of Control Theory Čelikovský Sergej UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0021057 Šebek M. CZ textový dokument 747 Kb cav_un_auth*0292613 GA13-20433S GA ČR This paper deals with identification of a building model based on real-life data and subsequent temperature controller design. For the identification, advanced identification technique - namely MPC Relevant Identification method - is used. This approach has the capability of providing models with better prediction performance compared to the commonly used methods. Regarding the controller part, several alternatives are proposed. First, both linear and nonlinear MPC controlling the zone temperature are designed. Although highly attractive due to promising energetic savings and thermal comfort satisfaction, MPCs demand high computational power. To overcome this issue and preserve the attractive properties of the MPC, two MPC-learned feedback controllers are proposed, one learned from LMPC and the other learned from NMPC. While remaining computationally low-cost, they improve the performance of the classical controllers towards the high-performance MPC standards. cav_un_auth*0318772 American Control Conference (ACC), 2015 01.07.2015-03.07.2015 Chicago US BC 2016 7 PR RVO:67985556 http://hdl.handle.net/11104/0248528 cav_un_auth*0300364 Department of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague ČVUT FEL v Praze CZ S n.a. Proceedings Paper Automation Control Systems|Engineering Electrical Electronic 0.565 Q2 2015 84940945621 SCOPUS 000370259201123 WOS textový dokument 747 Kb cav_un_epca*0446537 Proceedings of the American Control Conference 2015 978-1-4799-8684-2 0743-1619 1671 1676 Chicago, IL IEEE 2015