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Python Optimization Package

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July 04, 2015, at 12:48 PM by 45.56.3.184 -
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 git clone git://github.com/APMonitor/apm_python
July 04, 2015, at 12:20 PM by 45.56.3.184 -
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!! APM Python

Attach:apm_python.png APM Python is designed for large-scale optimization and accesses solvers of constrained, unconstrained, continuous, and discrete problems. Problems in linear programming, quadratic programming, integer programming, nonlinear optimization, systems of dynamic nonlinear equations, and multiobjective optimization can be solved. The platform can find optimal solutions, perform tradeoff analyses, balance multiple design alternatives, and incorporate optimization methods into external modeling and analysis software. It is free for academic and commercial use.
to:
Attach:apm_python.png APM Python is designed for large-scale optimization and accesses solvers of constrained, unconstrained, continuous, and discrete problems. Problems in linear programming, quadratic programming, integer programming, nonlinear optimization, systems of dynamic nonlinear equations, and multiobjective optimization can be solved. The platform can find optimal solutions, perform tradeoff analyses, balance multiple design alternatives, and incorporate optimization methods into external modeling and analysis software. It is free for academic and commercial use. Example applications of nonlinear models with differential and algebraic equations are available for download below or from the following GitHub repository.

Attach:download.jpg [[https://github.com/APMonitor?tab=repositories | APM Python with Demo Applications on GitHub]]

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* %list list-blogroll% [[https://github.com/jckantor/CBE40455/blob/master/notebooks/Getting%20Started%20with%20APMonitor.ipynb | APM IPython Notebook Example on GitHub]]
July 04, 2015, at 12:18 PM by 45.56.3.184 -
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(:title Nonlinear Optimization with Python:)
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(:title Python Optimization Package:)
April 29, 2015, at 07:45 AM by 45.56.3.184 -
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Attach:download.jpg [[Attach:apm_python_v0.7.0.zip | Download APM Python (version 0.7.0)]] - Released 30 Jan 2015
to:
Attach:download.jpg [[Attach:apm_python_v0.7.1.zip | Download APM Python (version 0.7.1)]] - Released 29 Apr 2015
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Attach:download.jpg [[Attach:apm_python_v0.6.1.zip | Download APM Python (version 0.6.1)]] - Released 5 May 2014
to:
Attach:download.jpg [[Attach:apm_python_v0.7.0.zip | Download APM Python (version 0.7.0)]] - Released 30 Jan 2015
May 05, 2014, at 10:32 PM by 23.255.240.62 -
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Attach:download.jpg [[Attach:apm_python_v0.6.0.zip | Download APM Python (version 0.6.0)]] - Released 20 January 2014
to:
Attach:download.jpg [[Attach:apm_python_v0.6.1.zip | Download APM Python (version 0.6.1)]] - Released 5 May 2014
January 20, 2014, at 08:30 AM by 23.255.228.67 -
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Attach:download.jpg [[Attach:apm_python_v0.5.8d.zip | Download APM Python (version 0.5.8d)]] - Released 25 March 2013
to:
Attach:download.jpg [[Attach:apm_python_v0.6.0.zip | Download APM Python (version 0.6.0)]] - Released 20 January 2014
June 27, 2013, at 05:08 PM by 128.187.97.18 -
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[[http://apmonitor.com/online/view_pass.php?f=hs071.apm|Solve this problem]] problem from a web-browser interface.
to:
* [[http://apmonitor.com/online/view_pass.php?f=hs071.apm|Solve this optimization problem from a web-browser interface]] or download the Python source above. The Python files are contained in folder ''example_hs71''.
June 27, 2013, at 05:06 PM by 128.187.97.18 -
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Hock-Schittkowsky Test Suite #71
to:
[[http://apmonitor.com/online/view_pass.php?f=hs071.apm|Solve this problem]] problem from a web-browser interface.
March 25, 2013, at 10:43 AM by 69.169.188.188 -
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Attach:download.jpg [[Attach:apm_python_v0.5.8.zip | Download APM Python (version 0.5.8)]] - Released 7 January 2013
to:
Attach:download.jpg [[Attach:apm_python_v0.5.8d.zip | Download APM Python (version 0.5.8d)]] - Released 25 March 2013
January 17, 2013, at 12:21 AM by 69.169.188.188 -
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* [[Main/PythonFunctions | APM Python Source Code Documentation]]
January 12, 2013, at 07:05 AM by 69.169.188.188 -
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(:html:)
<iframe width="560" height="315" src="http://www.youtube.com/embed/t84YMw8p34w?rel=0" frameborder="0" allowfullscreen></iframe>
(:htmlend:)
January 12, 2013, at 07:00 AM by 69.169.188.188 -
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Attach:apm_python.png Python offers a powerful scripting capabilities for solving nonlinear optimization problems.  The optimization problem is sent to the APMonitor server and results are returned to the Python script.  A web-interface to the solution helps to visualize the dynamic optimization problems.  Example applications of nonlinear models with differential and algebraic equations are available for download below.
to:
Attach:apm_python.png APM Python is designed for large-scale optimization and accesses solvers of constrained, unconstrained, continuous, and discrete problems. Problems in linear programming, quadratic programming, integer programming, nonlinear optimization, systems of dynamic nonlinear equations, and multiobjective optimization can be solved. The platform can find optimal solutions, perform tradeoff analyses, balance multiple design alternatives, and incorporate optimization methods into external modeling and analysis software. It is free for academic and commercial use.
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to:
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January 07, 2013, at 06:01 AM by 69.169.188.188 -
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Attach:download.jpg [[Attach:apm_python_v0.5.8.zip | Download APM Python (version 0.5.8)]] - Released 1 January 2013
to:
Attach:download.jpg [[Attach:apm_python_v0.5.8.zip | Download APM Python (version 0.5.8)]] - Released 7 January 2013
January 07, 2013, at 06:01 AM by 69.169.188.188 -
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Attach:download.jpg [[Attach:apm_python_v0.5.7.zip | Download APM Python (version 0.5.7)]] - Released 7 March 2012
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Attach:download.jpg [[Attach:apm_python_v0.5.8.zip | Download APM Python (version 0.5.8)]] - Released 1 January 2013
May 23, 2012, at 05:17 PM by 128.187.97.18 -
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Attach:download.jpg [[Attach:apm_python_v0.5.6.zip | Download APM Python (version 0.5.6)]] - Released 7 March 2012
to:
Attach:download.jpg [[Attach:apm_python_v0.5.7.zip | Download APM Python (version 0.5.7)]] - Released 7 March 2012
March 07, 2012, at 11:58 AM by 128.187.97.23 -
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Attach:download.jpg [[Attach:apm_python_v0.5.6.zip | Download APM Python (version 0.5.6)]] - Released 15 Feb 2012
to:
Attach:download.jpg [[Attach:apm_python_v0.5.6.zip | Download APM Python (version 0.5.6)]] - Released 7 March 2012
February 15, 2012, at 08:33 PM by 69.169.188.228 -
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Attach:download.jpg [[Attach:apm_python_v0.5.5.zip | Download APM Python (version 0.5.5)]] - Released 5 Dec 2011
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Attach:download.jpg [[Attach:apm_python_v0.5.6.zip | Download APM Python (version 0.5.6)]] - Released 15 Feb 2012
December 24, 2011, at 09:34 PM by 69.169.188.228 -
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(:description Use APMonitor with the power of Python scripting language:)

!! Python for APMonitor
to:
(:description APM Python: A comprehensive modeling and nonlinear optimization solution with Python scripting language:)

!! APM Python
December 21, 2011, at 11:20 PM by 69.169.188.228 -
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Attach:download.jpg [[Attach:apm_python_v0.5.5.zip | APM Python (version 0.5.5) Released 5 Dec 2011]]
to:
Attach:download.jpg [[Attach:apm_python_v0.5.5.zip | Download APM Python (version 0.5.5)]] - Released 5 Dec 2011
December 21, 2011, at 11:16 PM by 69.169.188.228 -
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The latest APM Python libraries are attached below.  Functionality has been tested with Python 2.7 and requires only the base [[http://www.python.org/getit/releases/2.7/ | Python installation]].  Example applications that use the apm.py library are listed further down on this page.
to:
The latest APM Python libraries are attached below.  Functionality has been tested with [[http://www.python.org/getit/releases/2.7/ | Python 2.7]].  Example applications that use the apm.py library are listed further down on this page.
December 21, 2011, at 11:15 PM by 69.169.188.228 -
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The development roadmap for this and other libraries are detailed in the [[Main/ProductRoadmap | release notes]] section.  The zipped archive contains the APM Python library '''apm.py''' and a number of example problems in separate folders.  Descriptions of the example problems are provided below.
to:
The development roadmap for this and other libraries are detailed in the [[Main/ProductRoadmap | release notes]].  The zipped archive contains the APM Python library '''apm.py''' and a number of example problems in separate folders.  Descriptions of the example problems are provided below.
December 21, 2011, at 11:14 PM by 69.169.188.228 -
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The product roadmap for this and other libraries are detailed in the [[Main/ProductRoadmap | release notes]] section.  The zipped archive contains the APM Python library '''apm.py''' and a number of example problems in separate folders.  Descriptions of the example problems are provided below.
to:
The development roadmap for this and other libraries are detailed in the [[Main/ProductRoadmap | release notes]] section.  The zipped archive contains the APM Python library '''apm.py''' and a number of example problems in separate folders.  Descriptions of the example problems are provided below.
December 21, 2011, at 11:10 PM by 69.169.188.228 -
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* %list list-blogroll% [[Apps/DistillationColumn | Distillation Column]]
December 21, 2011, at 09:03 PM by 69.169.188.228 -
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!!! Folder example_hs071: Nonlinear Programming with Python
to:
!!! Example_hs071: Nonlinear Programming with Python
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!!! Folder example_nlc: Nonlinear Control with Python
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!!! Example_nlc: Nonlinear Control with Python
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!!! Folder example_tank_mhe/nlc: Nonlinear Estimation and Control with Python
to:
!!! Example_tank_mhe/nlc: Nonlinear Estimation and Control with Python
December 21, 2011, at 09:02 PM by 69.169.188.228 -
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!!! Folder example_tank_mhe: Nonlinear Estimation and Control with Python
to:
!!! Folder example_tank_mhe/nlc: Nonlinear Estimation and Control with Python
December 21, 2011, at 09:01 PM by 69.169.188.228 -
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!!! Download APM Python Libraries
to:
!!! Download APM Python Library and Example Problems
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The zipped archives contain a single script file '''apm.py'''.  To use the APM Python library, include the following at the top of a Python script:

'''from apm import *'''

Previous versions
of the APM Python libraries are available below in the prior versions section.  In general, it is best to use the most current version as it supports the most advanced server features.  The product roadmap for this and other libraries are detailed in the [[Main/ProductRoadmap | release notes]] section.

''Prior Versions''

* [[Attach:apm_python_v0.5.4.zip | APM Python (version 0.5.4) Released 15 Sept 2011]]

Example applications of the APM Python library include nonlinear programming, nonlinear control, and other applications
below.
to:
The product roadmap for this and other libraries are detailed in the [[Main/ProductRoadmap | release notes]] section.  The zipped archive contains the APM Python library '''apm.py''' and a number of example problems in separate folders.  Descriptions of the example problems are provided below.
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!!! Nonlinear Programming with Python

Attach:download.jpg [[Attach:python_hs71.zip | APM Python for Nonlinear Optimization]]

to:
!!! Folder example_hs071: Nonlinear Programming with Python
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!!! Nonlinear Control with Python

Attach:download.jpg [[Attach:python_nlc.zip | APM Python Example for Nonlinear Control]]

to:
!!! Folder example_nlc: Nonlinear Control with Python
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!!! Nonlinear Estimation and Control with Python
to:
!!! Folder example_tank_mhe: Nonlinear Estimation and Control with Python
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The the unknown parameters ''c1'' and ''c2'' need to be determined.  The parameter ''c1'' is the flow into the tank when the valve is fully open.  The parameter ''c2'' is the relationship between the volume of water in the tank and the outlet flow.  Notice that this model is nonlinear because the outlet flow depends on the square root of the liquid volume.  Nonlinear estimation is a technique to determine parameters based on the measurements.  The following Python script uses the process data and the nonlinear model to determine the optimal parameters ''c1'' and ''c2''.

Attach:download.jpg [[Attach:python_tank_mhe.zip | Nonlinear Estimation of a Gravity Drained Tank]]

to:
The the unknown parameters ''c1'' and ''c2'' need to be determined.  The parameter ''c1'' is the flow into the tank when the valve is fully open.  The parameter ''c2'' is the relationship between the volume of water in the tank and the outlet flow.  This model is nonlinear because the outlet flow depends on the square root of the liquid volume.  Nonlinear estimation is a technique to determine parameters based on the measurements.  The script in '''example_tank_mhe''' uses the process data and the nonlinear model to determine the optimal parameters ''c1'' and ''c2''.
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After an accurate model of the process is obtained, the model can be used in a Nonlinear Control (NLC) application.  A PID controller is compared to the NLC response in the following script.

Attach:download.jpg [[Attach:python_tank_nlc.zip | Nonlinear Control of a Gravity Drained Tank]]
to:
After an accurate model of the process is obtained, the model can be used in a Nonlinear Control (NLC) application.  A PID controller is compared to the NLC response in the folder '''example_tank_nlc'''.
December 14, 2011, at 10:25 PM by 69.169.188.228 -
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The latest APM Python libraries are attached below.  Functionality has been tested with Python 2.7 and requires only the base [[http://www.python.org/getit/releases/2.7/ | Python installation]].
to:
The latest APM Python libraries are attached below.  Functionality has been tested with Python 2.7 and requires only the base [[http://www.python.org/getit/releases/2.7/ | Python installation]].  Example applications that use the apm.py library are listed further down on this page.
December 05, 2011, at 11:00 PM by 69.169.188.228 -
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Example applications of the APM Python library include nonlinear programming, nonlinear control, and other applications below.
December 05, 2011, at 10:59 PM by 69.169.188.228 -
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Previous versions of the APM Python libraries are available below.  In general, it is best to use the most current version as it supports the most advanced server features.  The product roadmap for this and other libraries are detailed in the [[Main/ProductRoadmap | release notes]] section.
to:
Previous versions of the APM Python libraries are available below in the prior versions section.  In general, it is best to use the most current version as it supports the most advanced server features.  The product roadmap for this and other libraries are detailed in the [[Main/ProductRoadmap | release notes]] section.

''Prior Versions''
December 05, 2011, at 10:57 PM by 69.169.188.228 -
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'''from apm import *''''
to:
'''from apm import *'''
December 05, 2011, at 10:46 PM by 69.169.188.228 -
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Attach:download.jpg [[Attach:apm_python_v0.5.5.zip | APM Python - v.0.5.5 - 5 Dec 2011]]
to:
Attach:download.jpg [[Attach:apm_python_v0.5.5.zip | APM Python (version 0.5.5) Released 5 Dec 2011]]
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* [[Attach:apm_python_v0.5.4.zip | APM Python - v.0.5.4 - 15 Sept 2011]]
to:
* [[Attach:apm_python_v0.5.4.zip | APM Python (version 0.5.4) Released 15 Sept 2011]]
December 05, 2011, at 10:45 PM by 69.169.188.228 -
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Attach:download.jpg [[Attach:python_hs71.zip | Download APM Python for Nonlinear Optimization]]
to:
Attach:download.jpg [[Attach:python_hs71.zip | APM Python for Nonlinear Optimization]]
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Attach:download.jpg [[Attach:python_nlc.zip | Download APM Python Package for Nonlinear Control]]
to:
Attach:download.jpg [[Attach:python_nlc.zip | APM Python Example for Nonlinear Control]]
December 05, 2011, at 10:41 PM by 69.169.188.228 -
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Previous versions of the APM Python libraries are available below.  In general, it is best to use the most current version as it supports the most advanced server features.

Attach:download.jpg
[[Attach:apm_python_v0.5.4.zip | APM Python - v.0.5.4 - 15 Sept 2011]]
to:
Previous versions of the APM Python libraries are available below.  In general, it is best to use the most current version as it supports the most advanced server features.  The product roadmap for this and other libraries are detailed in the [[Main/ProductRoadmap | release notes]] section.

*
[[Attach:apm_python_v0.5.4.zip | APM Python - v.0.5.4 - 15 Sept 2011]]
December 05, 2011, at 10:38 PM by 69.169.188.228 -
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The latest APM Python libraries are attached below.
to:
The latest APM Python libraries are attached below.  Functionality has been tested with Python 2.7 and requires only the base [[http://www.python.org/getit/releases/2.7/ | Python installation]].
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Attach:download.jpg [[Attach:apm_python_v0.5.4.zip | APM Python - v.0.5.4 - 15 Sept 2011]]
to:
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Previous versions of the APM Python libraries are available below.  In general, it is best to use the most current version as it supports the most advanced server features.

Attach:download.jpg [[Attach:apm_python_v0.5.4.zip | APM Python - v.0.5.4 - 15 Sept 2011]]
December 05, 2011, at 10:35 PM by 69.169.188.228 -
December 05, 2011, at 10:33 PM by 69.169.188.228 -
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!!! Download APM Python Libraries Versions

* [[Attach:apm_python_v0.5.5.zip | APM Python - v
.0.5.5 - Released 5 Dec 2011]]
* [[Attach:apm_python_v0.5.4.zip | APM Python -
v.0.5.4 - Released 15 Sept 2011]]
to:
!!! Download APM Python Libraries

The latest APM Python libraries are attached below
.

Attach:download
.jpg [[Attach:apm_python_v0.5.5.zip | APM Python - v.0.5.5 - 5 Dec 2011]]
Attach:download.jpg [[Attach:apm_python_v0.5.4.zip | APM Python - v.0.5.4 - 15 Sept 2011]]

The zipped archives contain a single script file '''apm.py'''.  To use the APM Python library, include the following at the top of a Python script:

'''from apm import *''''
December 05, 2011, at 10:29 PM by 69.169.188.228 -
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!!! Download APM Python Libraries Versions

* [[Attach:apm_python_v0.5.5.zip | APM Python - v.0.5.5 - Released 5 Dec 2011]]
* [[Attach:apm_python_v0.5.4.zip | APM Python - v.0.5.4 - Released 15 Sept 2011]]

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Attach:download.jpg [[Attach:python_hs71.zip | Download APM Python Package for Nonlinear Optimization]]
to:
Attach:download.jpg [[Attach:python_hs71.zip | Download APM Python for Nonlinear Optimization]]
November 08, 2011, at 03:58 AM by 69.169.188.228 -
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Python offers a powerful scripting capabilities for solving nonlinear optimization problems.  The optimization problem is sent to the APMonitor server and results are returned to the Python script.  A web-interface to the solution helps to visualize the dynamic optimization problems.  Example applications of nonlinear models with differential and algebraic equations are available for download below.
to:
Attach:apm_python.png Python offers a powerful scripting capabilities for solving nonlinear optimization problems.  The optimization problem is sent to the APMonitor server and results are returned to the Python script.  A web-interface to the solution helps to visualize the dynamic optimization problems.  Example applications of nonlinear models with differential and algebraic equations are available for download below.
September 26, 2011, at 04:13 PM by 69.169.188.228 -
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to:
* %list list-blogroll% [[Apps/StirredReactor | Stirred Reactor]]
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----
to:
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!!! Other Applications with Python

* %list list-blogroll% [[Apps/DiabeticGlucose | Diabetic Blood Glucose Control]]


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Attach:download.jpg [[Attach:python_tank_mhe.zip | Download APM Python Package for Nonlinear Estimation of a Gravity Drained Tank]]
to:
Attach:download.jpg [[Attach:python_tank_mhe.zip | Nonlinear Estimation of a Gravity Drained Tank]]
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Attach:download.jpg [[Attach:python_tank_nlc.zip | Download APM Python Package for Nonlinear Control of a Gravity Drained Tank]]
to:
Attach:download.jpg [[Attach:python_tank_nlc.zip | Nonlinear Control of a Gravity Drained Tank]]
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!!! Nonlinear Estimation and Control with Python

In this case study, a gravity drained tank was operated to generate data.  A dynamic model of the process was derived from a material balance.  This material balance is displayed below, along with a diagram of the system.

Attach:python_tank.png

The the unknown parameters ''c1'' and ''c2'' need to be determined.  The parameter ''c1'' is the flow into the tank when the valve is fully open.  The parameter ''c2'' is the relationship between the volume of water in the tank and the outlet flow.  Notice that this model is nonlinear because the outlet flow depends on the square root of the liquid volume.  Nonlinear estimation is a technique to determine parameters based on the measurements.  The following Python script uses the process data and the nonlinear model to determine the optimal parameters ''c1'' and ''c2''.

Attach:download.jpg [[Attach:python_tank_mhe.zip | Download APM Python Package for Nonlinear Estimation of a Gravity Drained Tank]]

Attach:python_tank_mhe.png

After an accurate model of the process is obtained, the model can be used in a Nonlinear Control (NLC) application.  A PID controller is compared to the NLC response in the following script.

Attach:download.jpg [[Attach:python_tank_nlc.zip | Download APM Python Package for Nonlinear Control of a Gravity Drained Tank]]

Attach:python_tank_nlc.png
July 10, 2011, at 03:02 PM by 89.144.73.196 -
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!!! Example #1: Hock-Schittkowsky Test Suite #71 with the IPOPT Solver
to:
!!! Nonlinear Programming with Python
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to:
Hock-Schittkowsky Test Suite #71
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!!! Example #2: Nonlinear Control with Python
to:
!!! Nonlinear Control with Python
July 10, 2011, at 02:33 PM by 89.144.73.196 -
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(:title Python Interface to APMonitor:)
to:
(:title Nonlinear Optimization with Python:)
July 10, 2011, at 02:31 PM by 89.144.73.196 -
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Attach:download.jpg [[Attach:python_hs71.zip | Download APM Python Source for Nonlinear Optimization]]
to:
Attach:download.jpg [[Attach:python_hs71.zip | Download APM Python Package for Nonlinear Optimization]]
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Attach:download.jpg [[Attach:python_nlc.zip | Download APM Python Source for Nonlinear Control]]
to:
Attach:download.jpg [[Attach:python_nlc.zip | Download APM Python Package for Nonlinear Control]]

Attach:python_nlc.png
July 10, 2011, at 02:24 PM by 89.144.73.196 -
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!!! Example #2: Nonlinear Control with Python with the APOPT solver
to:
!!! Example #2: Nonlinear Control with Python
July 10, 2011, at 02:23 PM by 89.144.73.196 -
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Attach:download.jpg [[Attach:python_hs71.zip | Download APM Python Interface Source for HS71]]
to:
Attach:download.jpg [[Attach:python_hs71.zip | Download APM Python Source for Nonlinear Optimization]]
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Attach:download.jpg [[Attach:python_nlc.zip | Download APM Python Interface Source for Nonlinear Control]]
to:
Attach:download.jpg [[Attach:python_nlc.zip | Download APM Python Source for Nonlinear Control]]
July 10, 2011, at 02:20 PM by 89.144.73.196 -
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(:title Python Interface to APMonitor:)
(:keywords nonlinear, Python, model, predictive control, APMonitor, differential, algebraic, modeling language:)
(:description Use APMonitor with the power of Python scripting language:)

!! Python for APMonitor

Python offers a powerful scripting capabilities for solving nonlinear optimization problems.  The optimization problem is sent to the APMonitor server and results are returned to the Python script.  A web-interface to the solution helps to visualize the dynamic optimization problems.  Example applications of nonlinear models with differential and algebraic equations are available for download below.

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!!! Example #1: Hock-Schittkowsky Test Suite #71 with the IPOPT Solver

Attach:download.jpg [[Attach:python_hs71.zip | Download APM Python Interface Source for HS71]]

Attach:hs71.gif

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!!! Example #2: Nonlinear Control with Python with the APOPT solver

Attach:download.jpg [[Attach:python_nlc.zip | Download APM Python Interface Source for Nonlinear Control]]

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