0460306 - ÚTIA 2017 RIV GB eng J - Journal Article
Pčolka, M. - Žáčeková, E. - Robinett, R. - Čelikovský, Sergej - Šebek, M.
Bridging the gap between the linear and nonlinear predictive control: Adaptations fo refficient building climate control.
Control Engineering Practice. Roč. 53, č. 1 (2016), s. 124-138. ISSN 0967-0661. E-ISSN 1873-6939
R&D Projects: GA ČR GA13-20433S
Institutional support: RVO:67985556
Keywords : Model predictive control * Identification for control * Building climatecontrol
Subject RIV: BC - Control Systems Theory
Impact factor: 2.602, year: 2016 ; AIS: 0.774, rok: 2016
Result website:
http://library.utia.cas.cz/separaty/2016/TR/celikovsky-0460306.pdf

DOI: https://doi.org/10.1016/j.conengprac.2016.01.007

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.
Permanent Link: http://hdl.handle.net/11104/0260442