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A state space error estimate for pod-deim nonlinear model reduction

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Date

2012

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Publisher

Siam Publications

Abstract

This paper derives state space error bounds for the solutions of reduced systems constructed using proper orthogonal decomposition (POD) together with the discrete empirical interpolation method (DEIM) recently developed for nonlinear dynamical systems [SIAM J. Sci. Comput., 32 (2010), pp. 2737-2764]. The resulting error estimates are shown to be proportional to the sums of the singular values corresponding to neglected POD basis vectors both in Galerkin projection of the reduced system and in the DEIM approximation of the nonlinear term. The analysis is particularly relevant to ODE systems arising from spatial discretizations of parabolic PDEs. The derivation clearly identifies where the parabolicity is crucial. It also explains how the DEIM approximation error involving the nonlinear term comes into play.

Description

Keywords

nonlinear model reduction, proper orthogonal decomposition, empirical, interpolation methods, nonlinear partial differential equations, proper orthogonal decomposition, partial-differential-equations, empirical interpolation method, reduced-order models, dynamical-systems, bounds, adaptivity, operators, mathematics, applied

Citation

Chaturantabut, S.; Sorensen, D. C., "A state space error estimate for pod-deim nonlinear model reduction," SIAM J. Numer. Anal., 50(1), 46-63, (2012). DOI: 10.1137/110822724