TY - GEN
T1 - Forty Plus Years of Model Reduction and Still Learning
AU - Astolff, A.
AU - Beck, C. L.
AU - Bhattacharjee, D.
AU - Kawano, Y.
AU - Moreschini, A.
AU - Sandberg, H.
AU - Scherpen, J. M.A.
N1 - This work has been partially supported by the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 739551 (KIOS CoE); by the Italian Ministry for Research in the framework of the 2020 Program for Research Projects of National Interest (PRIN), Grant 2020RTWES4; by the EPSRC grants EP/W005557 and EP/X033546; by NSF grant ECCS 20-32321, the Swedish Research Council under Grant 2016-00861; and by the JST FOREST Program Grant Number JPMJFR222E and JSPS KAKENHI Grant Number JP24K00910.
PY - 2024
Y1 - 2024
N2 - The approximation of complex dynamical systems models by reduced order models has been considered an important research problem for over four decades, not only in the field of control, but also in economics, image processing, circuit analysis, statistical mechanics, aircraft structures, and more recently in hybrid energy systems, to name just a sampling of fields. In this paper, we provide an overview of the development of balanced truncation and interpolation approaches for reducing linear and non-linear dynamical systems models for the purpose of control analysis and design.
AB - The approximation of complex dynamical systems models by reduced order models has been considered an important research problem for over four decades, not only in the field of control, but also in economics, image processing, circuit analysis, statistical mechanics, aircraft structures, and more recently in hybrid energy systems, to name just a sampling of fields. In this paper, we provide an overview of the development of balanced truncation and interpolation approaches for reducing linear and non-linear dynamical systems models for the purpose of control analysis and design.
UR - http://www.scopus.com/inward/record.url?scp=86000496338&partnerID=8YFLogxK
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U2 - 10.1109/CDC56724.2024.10886060
DO - 10.1109/CDC56724.2024.10886060
M3 - Conference contribution
AN - SCOPUS:86000496338
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 4480
EP - 4493
BT - 2024 IEEE 63rd Conference on Decision and Control, CDC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 63rd IEEE Conference on Decision and Control, CDC 2024
Y2 - 16 December 2024 through 19 December 2024
ER -