0460306 20240111140920.720160624235959.9 84956865804 000378955700012 10.1016/j.conengprac.2016.01.007 15 s. P cav_un_epca*02525960967-0661531 (2016)124-138Elsevier Model predictive control Identification for control Building climatecontrol cav_un_auth*0281469 Pčolka M. CZ cav_un_auth*0305702 Žáčeková E. 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 článek v odborném periodiku http://library.utia.cas.cz/separaty/2016/TR/celikovsky-0460306.pdf cav_un_auth*0292613 GA13-20433S GA ČR The linear model predictive control which is frequently used for building climate control benefits from the fact that the resulting optimization task is convex (thus easily and quickly solvable). On the other hand, the nonlinear model predictive control enables the use of a more detailed nonlinear model and it takes advantage of the fact that it addresses the optimization task more directly, however, it requires a more computationally complex algorithm for solving the non-convex optimization problem. In this paper,the gap between the linear and the nonlinear one is bridged by introducing apredictive controller with linear time-dependent model. Making use of linear time-dependent model of the building, the newly proposed controller obtains predictions which are closer to reality than those of linear time in-variant model, however,the computational complexity is still kept low since the optimization task remains convex. BC 2017 5 4 A hod 4ah 20231122141737.2 RVO:67985556 http://hdl.handle.net/11104/0260442 cav_un_auth*0300364 Department of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague ČVUT FEL v Praze CZ 1 Department of Control Theory UTIA-B 20205 AUTOMATION & CONTROL SYSTEMS S 2 Article|Proceedings Paper Automation Control Systems|Engineering Electrical Electronic AUTOMATION&CONTROLSYSTEMS|ENGINEERING.ELECTRICAL&ELECTRONIC 3.090 0.485 8.2 0.00838 0.774 6592 1.076 Q1 2.292 171 Q2 63.799 70.6 Q2 Q1 70.833 2016 Soubory v repozitáři: celikovsky-0460306.pdf 84956865804 SCOPUS 000378955700012 WOS článek v odborném periodiku cav_un_epca*0252596 Control Engineering Practice 0967-0661 1873-6939 Roč. 53 č. 1 2016 124 138 Elsevier