Model reduction procedure for stable nonlinear systems

Salim Ibrir; Maamar Bettayeb

doi:10.1109/IEEEGCC.2015.7060062

Model reduction procedure for stable nonlinear systems

Salim Ibrir
, Maamar Bettayeb

King Fahd University of Petroleum & Minerals

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

New model-reduction numerical procedure for a class of stable nonlinear systems is proposed. The proposed design is devoted to a spacial class of nonlinear systems whose nonlinearities are not necessarily Lipschitz with respect to its arguments. Additionally, the systems under consideration may contain uncertain parameters, having known lower and upper bounds. The computation of the reduced-model matrices is achieved by solving a set of linear matrix inequalities in iterative manner. An illustrative example is studied to approve the proposed theoretical results.

Original language	English
Title of host publication	2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479984220
DOIs	https://doi.org/10.1109/IEEEGCC.2015.7060062
State	Published - 12 Mar 2015

Publication series

Name	2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Convex Optimization
Model Reduction
Nonlinear Systems

ASJC Scopus subject areas

General Energy
General Engineering
General Computer Science

Access to Document

10.1109/IEEEGCC.2015.7060062

Cite this

@inproceedings{c7d21f6941534e0abd60385843d91725,

title = "Model reduction procedure for stable nonlinear systems",

abstract = "New model-reduction numerical procedure for a class of stable nonlinear systems is proposed. The proposed design is devoted to a spacial class of nonlinear systems whose nonlinearities are not necessarily Lipschitz with respect to its arguments. Additionally, the systems under consideration may contain uncertain parameters, having known lower and upper bounds. The computation of the reduced-model matrices is achieved by solving a set of linear matrix inequalities in iterative manner. An illustrative example is studied to approve the proposed theoretical results.",

keywords = "Convex Optimization, Model Reduction, Nonlinear Systems",

author = "Salim Ibrir and Maamar Bettayeb",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.",

year = "2015",

month = mar,

day = "12",

doi = "10.1109/IEEEGCC.2015.7060062",

language = "English",

series = "2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015",

address = "United States",

}

Model reduction procedure for stable nonlinear systems. / Ibrir, Salim; Bettayeb, Maamar.
2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7060062 (2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Model reduction procedure for stable nonlinear systems

AU - Ibrir, Salim

AU - Bettayeb, Maamar

PY - 2015/3/12

Y1 - 2015/3/12

N2 - New model-reduction numerical procedure for a class of stable nonlinear systems is proposed. The proposed design is devoted to a spacial class of nonlinear systems whose nonlinearities are not necessarily Lipschitz with respect to its arguments. Additionally, the systems under consideration may contain uncertain parameters, having known lower and upper bounds. The computation of the reduced-model matrices is achieved by solving a set of linear matrix inequalities in iterative manner. An illustrative example is studied to approve the proposed theoretical results.

AB - New model-reduction numerical procedure for a class of stable nonlinear systems is proposed. The proposed design is devoted to a spacial class of nonlinear systems whose nonlinearities are not necessarily Lipschitz with respect to its arguments. Additionally, the systems under consideration may contain uncertain parameters, having known lower and upper bounds. The computation of the reduced-model matrices is achieved by solving a set of linear matrix inequalities in iterative manner. An illustrative example is studied to approve the proposed theoretical results.

KW - Convex Optimization

KW - Model Reduction

KW - Nonlinear Systems

UR - https://www.scopus.com/pages/publications/84929121154

U2 - 10.1109/IEEEGCC.2015.7060062

DO - 10.1109/IEEEGCC.2015.7060062

M3 - Conference contribution

AN - SCOPUS:84929121154

T3 - 2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015

BT - 2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Model reduction procedure for stable nonlinear systems

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this