Optimal model reduction by time-domain moment matching for Lur'e-type models (extended version) - CRAN-CID Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Automatic Control Année : 2024

Optimal model reduction by time-domain moment matching for Lur'e-type models (extended version)

Résumé

This paper considers the problem of model reduction for Lur’e-type models consisting of a feedback interconnection between linear dynamics and static nonlinearities. We propose an optimal variant of the time-domain moment-matching method in which the Hinf-norm of the error transfer-function matrix of the linear part of the model is minimised, while the static nonlinearities are inherited from the full-order model. We show that this approach also minimises an error bound on the L2-norm of the steady state error between the responses of the full-order nonlinear model and the reduced order nonlinear model. Furthermore, the proposed approach preserves both the Lur’e-type model structure as well as global stability properties. The problem is cast as an optimisation problem with bilinear matrix inequality constraints. This problem is then solved using a novel algorithm, although global convergence of the algorithm is not guaranteed. The effectiveness of the approach is illustrated in the reduction of a structural dynamics model of a linear beam with nonlinear supports.
Fichier principal
Vignette du fichier
Shakib - Optimal model reduction by moment matching for Lur'e-type systems (extended version) - 2024.pdf (782.65 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04625393 , version 1 (26-06-2024)

Identifiants

  • HAL Id : hal-04625393 , version 1

Citer

Fahim Shakib, Giordano Scarciotti, Marc Jungers, Alexander Yu Pogromsky, Alexey Pavlov, et al.. Optimal model reduction by time-domain moment matching for Lur'e-type models (extended version). IEEE Transactions on Automatic Control, In press. ⟨hal-04625393⟩
0 Consultations
0 Téléchargements

Partager

Gmail Mastodon Facebook X LinkedIn More