Building Model - Revision history

Malhotra: infobox string

2023-11-30T09:26:18Z

infobox string

@@ Line 6: / Line 6: @@
 [[Category:second differential order]]
 [[Category:SISO]]
 ==Description: Motion Problem in a Building==

Mlinaric: Fix Python

2023-09-01T23:47:53Z

Fix Python

← Older revision		Revision as of 23:47, 1 September 2023
Line 33:		Line 33:
	A = mat['A'].toarray()		A = mat['A'].toarray()
	B = mat['B']		B = mat['B']
	C = mat['C'].astype(np.~~float_~~)		C = mat['C'].astype(np.float64)
	</syntaxhighlight>		</syntaxhighlight>

Mlinaric: Edit SLICOT link

2023-08-30T12:49:33Z

Edit SLICOT link

← Older revision		Revision as of 12:49, 30 August 2023
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	==Data==		==Data==

	The system matrices <math>A</math>, <math>B</math>, <math>C</math> are available from the [~~http~~://slicot.org/20-site/126-benchmark-examples-for-model-reduction SLICOT benchmarks] page: [https://www.slicot.org/objects/software/shared/bench-data/build.zip build.zip] and are stored as MATLAB [https://www.mathworks.com/help/matlab/import_export/mat-file-versions.html .mat] file.		The system matrices <math>A</math>, <math>B</math>, <math>C</math> are available from the [https://www.slicot.org/20-site/126-benchmark-examples-for-model-reduction SLICOT benchmarks] page: [https://www.slicot.org/objects/software/shared/bench-data/build.zip build.zip] and are stored as MATLAB [https://www.mathworks.com/help/matlab/import_export/mat-file-versions.html .mat] file.

	Here is [https://www.python.org Python] code for loading the matrices (<math>A</math> is stored as a sparse matrix that is mostly full and <math>C</math> is stored as an array of 8-bit unsigned integers):		Here is [https://www.python.org Python] code for loading the matrices (<math>A</math> is stored as a sparse matrix that is mostly full and <math>C</math> is stored as an array of 8-bit unsigned integers):

Mlinaric: Edit SLICOT link

2023-08-30T12:48:31Z

Edit SLICOT link

← Older revision		Revision as of 12:48, 30 August 2023
Line 22:		Line 22:
	==Data==		==Data==

	The system matrices <math>A</math>, <math>B</math>, <math>C</math> are available from the [http://slicot.org/20-site/126-benchmark-examples-for-model-reduction SLICOT benchmarks] page: [~~http~~://slicot.org/objects/software/shared/bench-data/build.zip build.zip] and are stored as MATLAB [https://www.mathworks.com/help/matlab/import_export/mat-file-versions.html .mat] file.		The system matrices <math>A</math>, <math>B</math>, <math>C</math> are available from the [http://slicot.org/20-site/126-benchmark-examples-for-model-reduction SLICOT benchmarks] page: [https://www.slicot.org/objects/software/shared/bench-data/build.zip build.zip] and are stored as MATLAB [https://www.mathworks.com/help/matlab/import_export/mat-file-versions.html .mat] file.

	Here is [https://www.python.org Python] code for loading the matrices (<math>A</math> is stored as a sparse matrix that is mostly full and <math>C</math> is stored as an array of 8-bit unsigned integers):		Here is [https://www.python.org Python] code for loading the matrices (<math>A</math> is stored as a sparse matrix that is mostly full and <math>C</math> is stored as an array of 8-bit unsigned integers):

Mlinaric: Edit categories, replace source tags

2023-08-29T16:37:54Z

Edit categories, replace source tags

← Older revision		Revision as of 16:37, 29 August 2023
Line 1:		Line 1:
	[[Category:benchmark]]		[[Category:benchmark]]
	[[Category:SLICOT]]		[[Category:SLICOT]]
	[[Category:~~Sparse~~]]		[[Category:linear]]
			[[Category:time invariant]]
			[[Category:first differential order]]
			[[Category:second differential order]]
	[[Category:SISO]]		[[Category:SISO]]

Line 23:		Line 26:
	Here is [https://www.python.org Python] code for loading the matrices (<math>A</math> is stored as a sparse matrix that is mostly full and <math>C</math> is stored as an array of 8-bit unsigned integers):		Here is [https://www.python.org Python] code for loading the matrices (<math>A</math> is stored as a sparse matrix that is mostly full and <math>C</math> is stored as an array of 8-bit unsigned integers):

	:<~~source~~ lang="python">		:<syntaxhighlight lang="python">
	import numpy as np		import numpy as np
	from scipy.io import loadmat		from scipy.io import loadmat
Line 31:		Line 34:
	B = mat['B']		B = mat['B']
	C = mat['C'].astype(np.float_)		C = mat['C'].astype(np.float_)
	</~~source~~>		</syntaxhighlight>

	The <math>(A, B, C)</math> represents a second-order system		The <math>(A, B, C)</math> represents a second-order system
Line 65:		Line 68:
	Here is [https://www.python.org Python] code for checking the structure and extracting the second-order matrices:		Here is [https://www.python.org Python] code for checking the structure and extracting the second-order matrices:

	:<~~source~~ lang="python">		:<syntaxhighlight lang="python">
	n = 48		n = 48
	n2 = n // 2		n2 = n // 2
Line 78:		Line 81:
	Bso = B[n2:]		Bso = B[n2:]
	Cso = C[:, n2:]		Cso = C[:, n2:]
	</~~source~~>		</syntaxhighlight>

	==Dimensions==		==Dimensions==

Mlinaric: Small fix, Python code, second-order form

2023-08-29T15:43:05Z

Small fix, Python code, second-order form

@@ Line 6: / Line 6: @@
 ==Description: Motion Problem in a Building==
-This benchmark models the displacement of a multi-storey building for example during an Earthquake.
+This benchmark models the displacement of a multi-story building for example during an Earthquake.
 More details can be found in <ref name="antoulas01"/> and <ref name="chahlaoui02"/>, <ref name="chahlaoui05"/>.
@@ Line 16: / Line 16: @@
 This benchmark is part of the '''SLICOT Benchmark Examples for Model Reduction'''<ref name="chahlaoui05"/>.
 ==Data==
@@ Line 22: / Line 21: @@
 The system matrices <math>A</math>, <math>B</math>, <math>C</math> are available from the [http://slicot.org/20-site/126-benchmark-examples-for-model-reduction SLICOT benchmarks] page: [http://slicot.org/objects/software/shared/bench-data/build.zip build.zip] and are stored as MATLAB [https://www.mathworks.com/help/matlab/import_export/mat-file-versions.html .mat] file.
 ==Dimensions==
 System structure:
 :<math>
-\begin{array}{rcl}
+\begin{align}
-\dot{x}(t) &=& Ax(t) + Bu(t) \\
+  \dot{x}(t) &= A x(t) + B u(t) \\
-y(t) &=& Cx(t)
+  y(t) &= C x(t)
-\end{array}
+\end{align}
 </math>
@@ Line 40: / Line 99: @@
 <math>C \in \mathbb{R}^{1 \times 48}</math>.
 ==Citation==

Lund: remove preliminary and stub warnings

2022-08-26T12:53:45Z

remove preliminary and stub warnings

← Older revision		Revision as of 12:53, 26 August 2022
Line 1:		Line 1:
	~~{{preliminary}} <!-- Do not remove -->~~

	[[Category:benchmark]]		[[Category:benchmark]]
	[[Category:SLICOT]]		[[Category:SLICOT]]
	[[Category:Sparse]]		[[Category:Sparse]]
	[[Category:SISO]]		[[Category:SISO]]

	~~'''This is a stub. Please expand.'''~~

	==Description: Motion Problem in a Building==		==Description: Motion Problem in a Building==

Himpe: init building

2018-08-20T13:00:31Z

init building

New page

{{preliminary}} 

[[Category:benchmark]]
[[Category:SLICOT]]
[[Category:Sparse]]
[[Category:SISO]]

'''This is a stub. Please expand.'''

==Description: Motion Problem in a Building==

This benchmark models the displacement of a multi-storey building for example during an Earthquake.
More details can be found in <ref name="antoulas01"/> and <ref name="chahlaoui02"/>, <ref name="chahlaoui05"/>.

===Earthquake Model===

==Origin==

This benchmark is part of the '''SLICOT Benchmark Examples for Model Reduction'''<ref name="chahlaoui05"/>.

==Data==

The system matrices <math>A</math>, <math>B</math>, <math>C</math> are available from the [http://slicot.org/20-site/126-benchmark-examples-for-model-reduction SLICOT benchmarks] page: [http://slicot.org/objects/software/shared/bench-data/build.zip build.zip] and are stored as MATLAB [https://www.mathworks.com/help/matlab/import_export/mat-file-versions.html .mat] file.

==Dimensions==

System structure:

:<math>
\begin{array}{rcl}
\dot{x}(t) &=& Ax(t) + Bu(t) \\
y(t) &=& Cx(t)
\end{array}
</math>

System dimensions:

<math>A \in \mathbb{R}^{48 \times 48}</math>,
<math>B \in \mathbb{R}^{48 \times 1}</math>,
<math>C \in \mathbb{R}^{1 \times 48}</math>.

==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_build,
title = {{SLICOT} - Subroutine Library in Systems and Control Theory},
organization = {Niconet e.V.}
address = <nowiki>{\url{http://www.slicot.org}}</nowiki>,
key = {SLICOT}
}

* For the background on the benchmark:

@ARTICLE{morAntSG01,
author = <nowiki>{A.C. Antoulas, D.C. Sorensen and S. Gugercin}</nowiki>,
title = {A survey of model reduction methods for large-scale systems},
journal = {Contemporary Mathematics},
volume = {280},
pages = {193--219},
year = {2001},
doi = {10.1090/conm/280}
}

==References==

<references>

<ref name="antoulas01"> A.C. Antoulas, D.C. Sorensen and S. Gugercin. [https://doi.org/10.1090/conm/280 A survey of model reduction methods for large-scale systems]. Contemporary Mathematics, 280: 193--219, 2001.</ref>

<ref name="chahlaoui02"> Y. Chahlaoui, P. Van Dooren, [http://eprints.maths.manchester.ac.uk/1040/1/ChahlaouiV02a.pdf A collection of Benchmark examples for model reduction of linear time invariant dynamical systems], Working Note 2002-2: 2002.</ref>

<ref name="chahlaoui05"> Y. Chahlaoui, P. Van Dooren, [https://doi.org/10.1007/3-540-27909-1_24 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.</ref>

</references>