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Interpolation-Based Model Order Reduction for Polynomial Systems

Peter Benner, Pawan Goyal

2021SIAM Journal on Scientific Computing30 citationsDOIOpen Access PDF

Abstract

In this work, we investigate a model-order reduction scheme for polynomial systems. We begin with defining the generalized multivariate transfer functions for the system. Based on this, we aim at constructing a reduced-order system, interpolating the defined generalized transfer functions at a given set of interpolation points. Furthermore, we provide a method, inspired by the Loewner approach for linear and (quadratic-)bilinear systems, to determine a good-quality reduced-order system in an automatic way. We also discuss the computational issues related to the proposed method and a potential application of a CUR matrix approximation in order to further speed up simulation of the reduced-order systems. We test the efficiency of the proposed method via two benchmark examples.

Topics & Concepts

Bilinear interpolationMathematicsInterpolation (computer graphics)Reduction (mathematics)PolynomialApplied mathematicsModel order reductionMathematical optimizationQuadratic equationLinear systemSet (abstract data type)Order (exchange)AlgorithmComputer scienceMathematical analysisStatisticsProgramming languageEconomicsGeometryAnimationComputer graphics (images)FinanceProjection (relational algebra)Model Reduction and Neural NetworksNumerical methods for differential equationsReal-time simulation and control systems
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