Modelling View on Numerical Uncertainty Quantification for Dynamical Systems

We present a modelling view on the numerical quantification of uncertainties in the solution of a dynamical system, which mostly consists in using a linearized update procedure for the covariance matrix. We regard the Fokker-Planck equation for the probability density of the states of the dynamical system as ground truth and the numerical method as surrogate model. We give an error estimate and show the connection to the numerical solution of ordinary differential equations. Finally, uncertainty quantification is interpreted as measurement.

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Journal
IFAC-PapersOnLine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.ifacol.2025.03.055
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
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article

Modelling View on Numerical Uncertainty Quantification for Dynamical Systems

Dirk Langemann, Katja Tüting
IFAC-PapersOnLine
Probabilistic and Robust Engineering Design
article

Modelling View on Numerical Uncertainty Quantification for Dynamical Systems

Dirk Langemann, Katja Tüting
article en

Abstract

We present a modelling view on the numerical quantification of uncertainties in the solution of a dynamical system, which mostly consists in using a linearized update procedure for the covariance matrix. We regard the Fokker-Planck equation for the probability density of the states of the dynamical system as ground truth and the numerical method as surrogate model. We give an error estimate and show the connection to the numerical solution of ordinary differential equations. Finally, uncertainty quantification is interpreted as measurement.

IFAC-PapersOnLineVol. 59(1)
Technische Universität Braunschweig (DE)
Openalex Percentile: Top 94%
Probabilistic and Robust Engineering Design
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