On the approximation of moments for nonlinear systems
| Autor: | Alessandro Astolfi, Nicolás Faedo, John V. Ringwood, Giordano Scarciotti |
|---|---|
| Přispěvatelé: | Royal Society |
| Rok vydání: | 2021 |
| Předmět: |
Differential equations
Technology Settore ING-INF/04 Differential equation Computer science Computation Linear systems Reduction (complexity) Automation & Control Systems Engineering Mathematical model Moment matching 0102 Applied Mathematics Nonlinear systems Applied mathematics steady state Electrical and Electronic Engineering Science & Technology MODEL-REDUCTION Linear system Engineering Electrical & Electronic weighted residual methods Computer Science Applications Generators Steady-state Moment (mathematics) Method of mean weighted residuals Nonlinear system 0906 Electrical and Electronic Engineering Industrial Engineering & Automation Control and Systems Engineering moments Signal generators Generator (mathematics) 0913 Mechanical Engineering |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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