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dc.contributor.authorBenner, Peteren
dc.contributor.authorGugercin, Serkanen
dc.contributor.authorWerner, Steffen W. R.en
dc.description.abstractIn this paper, we extend the structure-preserving interpolatory model reduction framework, originally developed for linear systems, to structured bilinear control systems. Specifically, we give explicit construction formulae for the model reduction bases to satisfy different types of interpolation conditions. First, we establish the analysis for transfer function interpolation for single-input single-output structured bilinear systems. Then, we extend these results to the case of multi-input multi-output structured bilinear systems by matrix interpolation. The effectiveness of our structure-preserving approach is illustrated by means of various numerical examples.en
dc.description.sponsorshipGerman Research Foundation (DFG)German Research Foundation (DFG) [2297, 1897]; National Science FoundationNational Science Foundation (NSF) [DMS-1439786, DMS-1720257, DMS-1819110]; Simons Foundation [50736]; Projekt DEALen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.subjectModel reductionen
dc.subjectBilinear systemsen
dc.subjectStructure-preserving approximationen
dc.subjectStructured interpolationen
dc.titleStructure-preserving interpolation of bilinear control systemsen
dc.typeArticle - Refereeden
dc.description.versionPublished versionen
dc.contributor.departmentAcademy of Integrated Scienceen
dc.description.notesOpen Access funding enabled and organized by Projekt DEAL. Benner and Werner were supported by the German Research Foundation (DFG) Research Training Group 2297 "MathCoRe," Magdeburg, and the German Research Foundation (DFG) Priority Program 1897: "Calm, Smooth and Smart - Novel Approaches for Influencing Vibrations by Means of Deliberately Introduced Dissipation." Gugercin was supported in parts by National Science Foundation under Grant No. DMS-1720257 and DMS-1819110. Part of this material is based upon work supported by the National Science Foundation under Grant No. DMS-1439786 and by the Simons Foundation Grant No. 50736 while Gugercin and Benner were in residence at the Institute for Computational and Experimental Research in Mathematics in Providence, RI, during the "Model and dimension reduction in uncertain and dynamic systems" program.en
dc.title.serialAdvances in Computational Mathematicsen

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Creative Commons Attribution 4.0 International
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