Model reduction of nonlinear systems subject to input disturbances

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The method of convex optimization is used as a tool for model reduction of a class of nonlinear systems in the presence of disturbances. It is shown that under some conditions the nonlinear disturbed system can be approximated by a reduced order nonlinear system with similar disturbance-output properties to the original plant. The proposed model reduction strategy preserves the nonlinearity and the input disturbance nature of the model. It guarantees a sufficiently small error between the outputs of the original and the reduced-order systems, and also maintains the properties of input-to-state stability. The matrices of the reduced order system are given in terms of a set of linear matrix inequalities (LMIs). The paper concludes with a demonstration of the proposed approach on model reduction of a nonlinear electronic circuit with additive disturbances.
Original languageEnglish (US)
Title of host publication2017 American Control Conference (ACC)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages3488-3493
Number of pages6
ISBN (Print)9781509059928
DOIs
StatePublished - Jul 10 2017

Bibliographical note

KAUST Repository Item: Exported on 2021-09-14
Acknowledgements: The research reported herein is supported by the King Abdullah University of Science and Technology (KAUST). The authors would like to thank Prof. Salim Ibrir from King Fahd University of Petroleum and Minerals (KFUPM) for most fruitful discussions that substantially improved the paper.

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