0438351 20240111140857.420150105235959.9 84964379836 000370073804049 10.1109/CDC.2014.7040034 6 s. C cav_un_epca*0438349978-1-4673-6088-34142-4147Los AngelesIEEE2014 Model predictive Control Nonlinear systems cav_un_auth*0305702 Žáčeková E. CZ cav_un_auth*0281469 Pčolka M. CZ 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 http://library.utia.cas.cz/separaty/2014/TR/celikovsky-0438351.pdf 459 kB cav_un_auth*0292613 GA13-20433S GA ČR In this paper, the task of finding an algorithm providing sufficiently excited data within the MPC framework is tackled. Such algorithm is expected to take action only when the re-identification is needed and it shall be used as the “least costly” closed loop identification experiment for MPC. The already existing approach based on maximization of the smallest eigenvalue of the information matrix increase is revised and an adaptation by introducing a semi-receding horizon principle is performed. Further, the optimization algorithm used for the maximization of the provided information is adapted such that the constraints on the maximal allowed control performance deterioration are handled more carefully and are incorporated directly into the process instead of using them just as a termination condition. The effect of the performed adaptations is inspected using a numerical example. cav_un_auth*0312094 The 53rd IEEE Conference on Decision and Control (CDC 2014) 15.12.2014-17.12.2014 Los Angeles US BC 2015 4 PR RVO:67985556 http://hdl.handle.net/11104/0241783 cav_un_auth*0305697 Czech Technical University in Prague, Faculty of Electrical Engineering, Department of Control Engineering ČVUT v Praze, FEL, Katedra řídicí techniky CZ S 2014 84964379836 SCOPUS 000370073804049 WOS textový dokument 459 kB cav_un_epca*0438349 Proceedings of the 53rd IEEE Conference on Decision and Control (CDC 2014) 978-1-4673-6088-3 4142 4147 Los Angeles IEEE 2014 CFP14CDC-USB Catalog Number: CFP14CDC-CDR