bibtype	C - Conference Paper (international conference)
ARLID	0446538
utime	20240111140906.4
mtime	20150818235959.9
SCOPUS	84940945621
WOS	000370259201123
DOI	10.1109/ACC.2015.7170973
title (primary) (eng)	Identification and Energy Efficient Control for a Building: Getting Inspired by MPC
specification	page_count 6 s. media_type C
serial	ARLID cav_un_epca*0446537 ISBN 978-1-4799-8684-2 ISSN 0743-1619 title Proceedings of the American Control Conference 2015 page_num 1671-1676 publisher place Chicago, IL name IEEE year 2015
keyword	Identification
keyword	Model predictive control
keyword	Building climate control
author (primary)	ARLID cav_un_auth*0305702 name1 Žáčeková name2 E. country CZ
author	ARLID cav_un_auth*0281469 name1 Pčolka name2 M. country CZ
author	ARLID cav_un_auth*0318861 name1 Tabaček name2 J. country CZ
author	ARLID cav_un_auth*0318862 name1 Těžký name2 J. country CZ
author	ARLID cav_un_auth*0304632 name1 Robinett name2 R. country US
author	ARLID cav_un_auth*0101074 full_dept (cz) Teorie řízení full_dept Department of Control Theory department (cz) TŘ department TR full_dept Department of Control Theory name1 Čelikovský name2 Sergej institution UTIA-B fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author	ARLID cav_un_auth*0021057 name1 Šebek name2 M. country CZ
source	source_type textový dokument source_size 747 Kb
cas_special	project ARLID cav_un_auth*0292613 project_id GA13-20433S agency GA ČR abstract (eng) 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. action ARLID cav_un_auth*0318772 name American Control Conference (ACC), 2015 dates 01.07.2015-03.07.2015 place Chicago country US RIV BC reportyear 2016 num_of_auth 7 presentation_type PR inst_support RVO:67985556 permalink http://hdl.handle.net/11104/0248528 cooperation ARLID cav_un_auth*0300364 name Department of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague institution ČVUT FEL v Praze country CZ confidential S mrcbC86 n.a. Proceedings Paper Automation Control Systems|Engineering Electrical Electronic mrcbT16-s 0.565 mrcbT16-E Q2 arlyear 2015 mrcbU14 84940945621 SCOPUS mrcbU34 000370259201123 WOS mrcbU56 textový dokument 747 Kb mrcbU63 cav_un_epca*0446537 Proceedings of the American Control Conference 2015 978-1-4799-8684-2 0743-1619 1671 1676 Chicago, IL IEEE 2015