Results 21 to 30 of about 179,380 (196)
Extending dynamic mode decomposition to data from multiple outputs
, 2021 System identification based on Koopman operator theory has grown in popularity recently. Spectral properties of the Koopman operator of a system were proven to relate to properties like invariant sets, stability, periodicity, etc. of the underlying system.
Nibodh Boddupalli
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AIP AdvancesTo enhance the accuracy and efficiency of transient temperature rise and hot-spot temperature calculations for oil-immersed transformer windings, this study proposes an extended dynamic mode decomposition computational strategy.
Kexin Liu +6 more
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A concise introduction to Koopman operator theory and the Extended Dynamic Mode Decomposition [PDF]
13 pages, subject introduction ...
Christophe Patyn, Geert Deconinck
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IFAC-PapersOnLine, 2018 Abstract Data-based assessment of dynamic performances has attracted a lot of interest in the modern power system with high-accurate measurement technologies such as Synchrophasor. In this paper, we report the research effort to do this for voltage dynamics in a rudimentary model of power systems.
Yoshihiko Susuki, Kyoichi Sako
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$L^\infty$-error bounds for approximations of the Koopman operator by kernel extended dynamic mode decomposition [PDF]
Extended dynamic mode decomposition (EDMD) is a well-established method to generate a data-driven approximation of the Koopman operator for analysis and prediction of nonlinear dynamical systems. Recently, kernel EDMD (kEDMD) has gained popularity due to its ability to resolve the challenging task of choosing a suitable dictionary by using the kernel's
Frederik Köhne +4 more
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Orthogonal Polynomial Approximation and Extended Dynamic Mode Decomposition in Chaos
SIAM Journal on Numerical AnalysisExtended Dynamic Mode Decomposition (EDMD) is a data-driven tool for forecasting and model reduction of dynamics, which has been extensively taken up in the physical sciences. While the method is conceptually simple, in deterministic chaos it is unclear what its properties are or even what it converges to.
Caroline L. Wormell
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Efficient Nonlinear Model Predictive Control of Automated Vehicles
Mathematics, 2022 In this paper, an efficient model predictive control (MPC) of velocity tracking of automated vehicles is proposed, in which a reference signal is given a priori.
Shuyou Yu +5 more
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Mathematics, 2021 The extended dynamic mode decomposition algorithm is a tool for accurately approximating the point spectrum of the Koopman operator. This algorithm provides an approximate linear expansion of non-linear discrete-time systems, which can be useful for ...
Camilo Garcia-Tenorio +3 more
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Analysis of the ROA of an anaerobic digestion process via data-driven Koopman operator
Nonlinear Engineering, 2021 Nonlinear biochemical systems such as the anaerobic digestion process experience the problem of the multi-stability phenomena, and thus, the dynamic spectrum of the system has several undesired equilibrium states.
Garcia-Tenorio Camilo +3 more
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Data Science in Finance and Economics, 2022 We consider dynamical systems that have emerged in financial studies and exhibit chaotic behaviour. The main purpose is to develop a data-based method for reconstruction of the trajectories of these systems.
John Leventides +3 more
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