On the approximation of moments for nonlinear systems
File(s)
Accepted version
Author(s)
Faedo, Nicolás
Scarciotti, Giordano
Astolfi, Astolfi
Ringwood, John V
Type
Journal Article
Abstract
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 note 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.
Date Issued
2021-11-01
Date Acceptance
2021-01-10
Citation
IEEE Transactions on Automatic Control, 2021, 66 (11), pp.5538-5545
ISSN
0018-9286
Publisher
Institute of Electrical and Electronics Engineers
Start Page
5538
End Page
5545
Journal / Book Title
IEEE Transactions on Automatic Control
Volume
66
Issue
11
Copyright Statement
© 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.
Sponsor
Royal Society
Grant Number
IEC\R1\180018
Subjects
Science & Technology
Technology
Automation & Control Systems
Engineering, Electrical & Electronic
Engineering
Signal generators
Mathematical model
Nonlinear systems
Generators
Differential equations
Steady-state
Linear systems
Moment matching
moments
nonlinear systems
steady state
weighted residual methods
MODEL-REDUCTION
Industrial Engineering & Automation
0102 Applied Mathematics
0906 Electrical and Electronic Engineering
0913 Mechanical Engineering
Publication Status
Published
Date Publish Online
2021-01-25