A novel Krylov method for model order reduction of quadratic bilinear systems
| Autor: | Xingang Cao, Joseph M. Maubach, Wil H. A. Schilders, Siep Weiland |
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| Přispěvatelé: | Center for Analysis, Scientific Computing & Appl., Control Systems, Control of high-precision mechatronic systems, Spatial-Temporal Systems for Control, Cyber-Physical Systems Center Eindhoven |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Model order reduction
0209 industrial biotechnology Computational complexity theory Dynamical systems theory Computer science Quadratic-bilinear systems MathematicsofComputing_NUMERICALANALYSIS Bilinear interpolation Krylov methods 010103 numerical & computational mathematics 02 engineering and technology Krylov subspace 01 natural sciences Projection (linear algebra) 020901 industrial engineering & automation Quadratic equation Applied mathematics 0101 mathematics Interpolation |
| Zdroj: | 2018 IEEE Conference on Decision and Control, CDC 2018, 3217-3222 STARTPAGE=3217;ENDPAGE=3222;TITLE=2018 IEEE Conference on Decision and Control, CDC 2018 CDC |
| Popis: | A novel Krylov subspace method is proposed to substantially reduce the computational complexity of the special class of quadratic bilinear dynamical systems. Based on the first two generalized transfer functions of the system, a Petrov-Galerkin projection scheme is applied. It is shown that such a projection amounts to interpolating the transfer functions at specific points which, in fact, is equivalent to constructing the corresponding Krylov subspace. For single-input single-output systems, the relevant Krylov subspace can be readily constructed for the interpolation points. For multi-input multi-output systems, also user-specified directional information is required so that a tangential interpolation can be determined. The method is demonstrated by numerical examples. |
| Databáze: | OpenAIRE |
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