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The Koopman Operator (KO) provides an analytical solution of dynamical systems in terms of orthogonal polynomials. This work exploits this representation to include the propagation of uncertainties, where the polynomials are modified to work with stochastic variables. Thus, a new uncertainty quantification technique is proposed, where the KO solution is expanded to include the prediction of central moments, up to an arbitrary order. The propagation of uncertainties is then expanded to develop a new filtering algorithm, where measurements are considered as additional observables in the KO mathematics. Numerical simulations in astrodynamics assess the accuracy and performance of the new methodologies.
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Servadio et al. (Mon,) studied this question.
synapsesocial.com/papers/68e5ec3cb6db643587580bad — DOI: https://doi.org/10.48550/arxiv.2407.20052
Simone Servadio
Iowa State University
William E. Parker
IIT@MIT
Richard Linares
American Institute of Aeronautics and Astronautics
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