Gain scheduling for nonlinear systems via integral quadratic constraints

Bela Takarics, Peter Seiler

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

12 Scopus citations


The paper considers a general approach for gain scheduling of Lipschitz continuous nonlinear systems. The approach is based on a linear parameter varying system (LPV) representation of the nonlinear dynamics along with integral quadratic constraints (IQC) to account for the linearization errors. Past results have shown that Jacobian linearization leads to hidden coupling terms in the controlled system. These terms arise due to neglecting the higher order terms of the Taylor series and due to the use of constant (frozen) values of the scheduling parameter. This paper proposes an LPV control synthesis method that accounts for these shortcomings. The higher order terms of the linearization are treated as a memoryless uncertainty whose input/output behavior is described by a parameter varying IQC. It is also shown that if the rate of the scheduling parameter is measurable then it can be treated as a known disturbance in the control synthesis step. A simple numerical example shows that the proposed control design approach leads to improved control performance.

Original languageEnglish (US)
Title of host publicationACC 2015 - 2015 American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781479986842
StatePublished - Jul 28 2015
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: Jul 1 2015Jul 3 2015

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Conference2015 American Control Conference, ACC 2015
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2015 American Automatic Control Council.


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