Published January 25, 2021 | Version v1

On the Approximation of Moments for Nonlinear Systems

Description

Model reduction by moment-matching relies upon the availability of the so-called moment . If the system is nonlinear, the computation of moments depends on an underlying specific invariance equation, which can be difficult or impossible to solve. This article presents four technical contributions related to the theory of moment matching: first, we identify a connection between moment-based theory and weighted residual methods. Second, we exploit this relation to provide an approximation technique for the computation of nonlinear moments. Third, we extend the definition of nonlinear moment to the case in which the generator is described in explicit form. Finally, we provide an approximation technique to compute the moments in this scenario. The results are illustrated by means of two examples.

Notes

2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. N. Faedo, G. Scarciotti, A. Astolfi, and J. V. Ringwood, "On the Approximation of Moments for Nonlinear Systems," IEEE Transactions on Automatic Control, vol. 66, no. 11, pp. 5538-5545, Nov. 2021, doi: 10.1109/TAC.2021.3054325.

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Funding

European Commission
KIOS CoE - KIOS Research and Innovation Centre of Excellence 739551