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MORLAB – A Model Order Reduction Framework in MATLAB and Octave
When synthesizing feedback controllers for large-scale dynamical systems, often a reduction of the plant model by model order reduction is required. This is a typical task in computer-aided control system design environments. Therefore, in the last years, model order reduction became an essential to...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340936/ http://dx.doi.org/10.1007/978-3-030-52200-1_43 |
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author | Benner, Peter Werner, Steffen W. R. |
author_facet | Benner, Peter Werner, Steffen W. R. |
author_sort | Benner, Peter |
collection | PubMed |
description | When synthesizing feedback controllers for large-scale dynamical systems, often a reduction of the plant model by model order reduction is required. This is a typical task in computer-aided control system design environments. Therefore, in the last years, model order reduction became an essential tool for the practical use of mathematical models in engineering processes. For the integration of established model order reduction methods into those processes, software solutions are needed. In this paper, we describe the MORLAB (Model Order Reduction LABoratory) toolbox as such a software solution in MathWorks MATLAB(®) and GNU Octave, and its featured integration into established software tools used in simulations and controller design. We give benchmark examples for two important extensions of the toolbox. |
format | Online Article Text |
id | pubmed-7340936 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73409362020-07-08 MORLAB – A Model Order Reduction Framework in MATLAB and Octave Benner, Peter Werner, Steffen W. R. Mathematical Software – ICMS 2020 Article When synthesizing feedback controllers for large-scale dynamical systems, often a reduction of the plant model by model order reduction is required. This is a typical task in computer-aided control system design environments. Therefore, in the last years, model order reduction became an essential tool for the practical use of mathematical models in engineering processes. For the integration of established model order reduction methods into those processes, software solutions are needed. In this paper, we describe the MORLAB (Model Order Reduction LABoratory) toolbox as such a software solution in MathWorks MATLAB(®) and GNU Octave, and its featured integration into established software tools used in simulations and controller design. We give benchmark examples for two important extensions of the toolbox. 2020-06-06 /pmc/articles/PMC7340936/ http://dx.doi.org/10.1007/978-3-030-52200-1_43 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Benner, Peter Werner, Steffen W. R. MORLAB – A Model Order Reduction Framework in MATLAB and Octave |
title | MORLAB – A Model Order Reduction Framework in MATLAB and Octave |
title_full | MORLAB – A Model Order Reduction Framework in MATLAB and Octave |
title_fullStr | MORLAB – A Model Order Reduction Framework in MATLAB and Octave |
title_full_unstemmed | MORLAB – A Model Order Reduction Framework in MATLAB and Octave |
title_short | MORLAB – A Model Order Reduction Framework in MATLAB and Octave |
title_sort | morlab – a model order reduction framework in matlab and octave |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340936/ http://dx.doi.org/10.1007/978-3-030-52200-1_43 |
work_keys_str_mv | AT bennerpeter morlabamodelorderreductionframeworkinmatlabandoctave AT wernersteffenwr morlabamodelorderreductionframeworkinmatlabandoctave |