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Mini-Workshop: Data-driven Modeling, Analysis, and Control of Dynamical Systems

dc.date.accessioned2025-05-30T05:21:09Z
dc.date.available2025-05-30T05:21:09Z
dc.date.issued2024
dc.identifier.urihttp://publications.mfo.de/handle/mfo/4273
dc.description.abstractWith the rapid increase in data resources and computational power as well as the accompanying current trend to incorporate machine learning into existing methods, data-driven approaches for modelling, analysis, and control of dynamical systems have attracted new interest and opened doors to novel applications. However, there is always a discrepancy between mathematical models and reality such that rigorously-shown error bounds and uncertainty quantification are indispensable for a reliable use of data-driven techniques, e.g., using surrogate models in optimisation-based control. Similar comments apply to data-enhanced models. Consequently, uncertainty about parameters, the model itself and numerous other aspects need to be taken into account, e.g., in data-driven control of (stochastic) dynamical systems. Hence, the respective paradigm changes have led to a variety of novel concepts which, however, still suffer from limitations: many concentrate only on a single aspect, are only applicable to systems of limited complexity, or lack a sound mathematical foundation including guarantees on feasibility, robustness, or the overall performance. Pushing these limits, we face a wide spectrum of theoretic and algorithmic challenges in modeling, analysis, and control under uncertainty using data-driven methods.
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/*
dc.titleMini-Workshop: Data-driven Modeling, Analysis, and Control of Dynamical Systems
dc.rights.licenseUnless otherwise noted, the content of this report is licensed under Creative Commons Attribution-ShareAlike 4.0 International.*
dc.identifier.doi10.14760/OWR-2024-57
local.series.idOWR-2024-57
local.subject.msc93
local.subject.msc37
local.subject.msc47
local.subject.msc49
local.subject.msc68
local.date-range08 Dec - 13 Dec 2024
local.workshopcode2450c
local.workshoptitleMini-Workshop: Data-driven Modeling, Analysis, and Control of Dynamical Systems
local.organizersClarence W. Rowley, Princeton; Claudia Schillings, Berlin; Karl Worthmann, Ilmenau
local.report-nameWorkshop Report 2024,57
local.opc-photo-id2450c
local.publishers-doi10.4171/OWR/2024/57


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