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' | {{Infobox | ||
|Title = Penzl's FOM | |||
|Benchmark ID = penzlFOM_n1006m1q1 | |||
|Category = slicot | |||
|System-Class = LTI-FOS | |||
|nstates = 1006 | |||
|ninputs = 1 | |||
|noutputs = 1 | |||
|nparameters = 0 | |||
|components = A, B, C | |||
|License = NA | |||
|Creator = [[User:Himpe]] | |||
|Editor = | |||
* [[User:Himpe]] | |||
* [[User:Yue]] | |||
|Zenodo-link = NA | |||
}} | |||
==Description== | |||
== | This benchmark is an artificial example system of order <math>1006</math> from <ref name="penzl06"/> also listed in <ref name="chahlaoui02"/>. It has long been regarded as a standard "full order model" (FOM) for testing new methods. | ||
The benchmark system consists of the following system components: | The benchmark system consists of the following system components: | ||
<math> | <math> | ||
\begin{array}{rcl} | \begin{array}{rcl} | ||
A &=& \begin{pmatrix} A_1 \\ & A_2 \\ & & A_3 \\ & & & A_4 \end{pmatrix}, \ | A &=& \begin{pmatrix} A_1 \\ & A_2 \\ & & A_3 \\ & & & A_4 \end{pmatrix}, \\ | ||
A_1 = \begin{pmatrix} -1 & 100 \\ -100 & -1 \end{pmatrix}, \; | A_1 &=& \begin{pmatrix} -1 & 100 \\ -100 & -1 \end{pmatrix}, \; | ||
A_2 = \begin{pmatrix} -1 & 200 \\ -200 & -1 \end{pmatrix}, \; | A_2 = \begin{pmatrix} -1 & 200 \\ -200 & -1 \end{pmatrix}, \; | ||
A_3 = \begin{pmatrix} -1 & 400 \\ -400 & -1 \end{pmatrix}, \; | A_3 = \begin{pmatrix} -1 & 400 \\ -400 & -1 \end{pmatrix}, \; | ||
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</math> | </math> | ||
This system is a theoretical construct, but features a non-smooth [[wikipedia:Bode_plot|Bode plot]] with three spikes. | |||
===MIMO Variant=== | ===MIMO Variant=== | ||
| Line 33: | Line 49: | ||
===Parametric Variant=== | ===Parametric Variant=== | ||
In, a parametric variant of this benchmark is | In <ref name="Ionita14"/>, a parametric variant of this benchmark is formulated by redefining | ||
<math> | <math> | ||
A_1 = \begin{pmatrix} -1 & p \\ -p & -1 \end{pmatrix}. | A_1 = \begin{pmatrix} -1 & p \\ -p & -1 \end{pmatrix}. | ||
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<ref name="penzl06"> T. Penzl. <span class="plainlinks">[https://doi.org/10.1016/j.laa.2006.01.007 Algorithms for Model Reduction of Large Dynamical Systems]</span>. Linear Algebra and its Application 415(2--3): 322--343, 2006.</ref> | <ref name="penzl06"> T. Penzl. <span class="plainlinks">[https://doi.org/10.1016/j.laa.2006.01.007 Algorithms for Model Reduction of Large Dynamical Systems]</span>. Linear Algebra and its Application 415(2--3): 322--343, 2006.</ref> | ||
<ref name="heyouni08"> M. Heyouni, K. Jbilou, A. Messaoudi, K. Tabaa. <span class="plainlinks">[https:// | <ref name="heyouni08"> M. Heyouni, K. Jbilou, A. Messaoudi, K. Tabaa. <span class="plainlinks">[https://www.scielo.br/j/cam/a/Sq6GFZqcXSwNQKk3SmpB46p/?lang=en Model Reduction in Large-Scale MIMO Dynamical Systems via the Block Lanczos Method]</span>. Computational & Applied Mathematics 27(11): 211--236, 2008.</ref> | ||
<ref name="chahlaoui02"> Y. Chahlaoui, P. Van Dooren, <span class="plainlinks">[http://eprints.maths.manchester.ac.uk/1040/1/ChahlaouiV02a.pdf A collection of Benchmark examples for model reduction of linear time invariant dynamical systems]</span>, Working Note 2002-2: 2002.</ref> | <ref name="chahlaoui02"> Y. Chahlaoui, P. Van Dooren, <span class="plainlinks">[http://eprints.maths.manchester.ac.uk/1040/1/ChahlaouiV02a.pdf A collection of Benchmark examples for model reduction of linear time invariant dynamical systems]</span>, Working Note 2002-2: 2002.</ref> | ||
<ref name="chahlaoui05"> Y. Chahlaoui, P. Van Dooren, <span class="plainlinks">[https://doi.org/10.1007/3-540-27909-1_24 Benchmark Examples for Model Reduction of Linear Time-Invariant Dynamical Systems]</span>, Dimension Reduction of Large-Scale Systems, Lecture Notes in Computational Science and Engineering, vol 45: 379--392, 2005.</ref> | <ref name="chahlaoui05"> Y. Chahlaoui, P. Van Dooren, <span class="plainlinks">[https://doi.org/10.1007/3-540-27909-1_24 Benchmark Examples for Model Reduction of Linear Time-Invariant Dynamical Systems]</span>, Dimension Reduction of Large-Scale Systems, Lecture Notes in Computational Science and Engineering, vol 45: 379--392, 2005.</ref> | ||
<ref name="Ionita14"> A. C. Ionita,A. C. Antoulas, <span class="plainlinks">[https://doi.org/10.1137/130914619 Data-Driven Parametrized Model Reduction in the Loewner Framework]</span>, SIAM J. Sci. Comput. 36(3): A984–A1007, 2014.</ref> | |||
</references> | </references> | ||
Latest revision as of 09:38, 30 November 2023
| Background | |
|---|---|
| Benchmark ID |
penzlFOM_n1006m1q1 |
| Category |
slicot |
| System-Class |
LTI-FOS |
| Parameters | |
| nstates |
1006
|
| ninputs |
1 |
| noutputs |
1 |
| nparameters |
0 |
| components |
A, B, C |
| Copyright | |
| License |
NA |
| Creator | |
| Editor | |
| Location | |
|
NA | |
Description
This benchmark is an artificial example system of order from [1] also listed in [2]. It has long been regarded as a standard "full order model" (FOM) for testing new methods.
The benchmark system consists of the following system components:
This system is a theoretical construct, but features a non-smooth Bode plot with three spikes.
MIMO Variant
In [3] a MIMO variant of this benchmark is utilized by adding random vectors to and .
Parametric Variant
In [4], a parametric variant of this benchmark is formulated by redefining
Origin
This benchmark is part of the SLICOT Benchmark Examples for Model Reduction[5].
Data
The system matrices , , are available from the SLICOT benchmarks page: fom.zip and are stored as MATLAB .mat file.
Dimensions
System structure:
System dimensions:
, , ,
Citation
To cite this benchmark, use the following references:
- For the benchmark itself and its data:
- Niconet e.V., SLICOT - Subroutine Library in Systems and Control Theory, http://www.slicot.org
@MANUAL{slicot_fom,
title = {{SLICOT} - Subroutine Library in Systems and Control Theory},
organization = {Niconet e.V.}
address = {\url{http://www.slicot.org}},
key = {SLICOT}
}
- For the background on the benchmark:
@ARTICLE{morPen06,
author = {T. Penzl},
title = {Algorithms for Model Reduction of Large Dynamical Systems},
journal = {Linear Algebra and its Application},
volume = {415},
number = {2--3},
pages = {322--343},
year = {2006},
doi = {10.1016/j.laa.2006.01.007}
}
References
- ↑ T. Penzl. Algorithms for Model Reduction of Large Dynamical Systems. Linear Algebra and its Application 415(2--3): 322--343, 2006.
- ↑ Y. Chahlaoui, P. Van Dooren, A collection of Benchmark examples for model reduction of linear time invariant dynamical systems, Working Note 2002-2: 2002.
- ↑ M. Heyouni, K. Jbilou, A. Messaoudi, K. Tabaa. Model Reduction in Large-Scale MIMO Dynamical Systems via the Block Lanczos Method. Computational & Applied Mathematics 27(11): 211--236, 2008.
- ↑ A. C. Ionita,A. C. Antoulas, Data-Driven Parametrized Model Reduction in the Loewner Framework, SIAM J. Sci. Comput. 36(3): A984–A1007, 2014.
- ↑ Y. Chahlaoui, P. Van Dooren, Benchmark Examples for Model Reduction of Linear Time-Invariant Dynamical Systems, Dimension Reduction of Large-Scale Systems, Lecture Notes in Computational Science and Engineering, vol 45: 379--392, 2005.