| Name | control JSON |
| Version |
0.10.0
JSON |
| download |
| home_page | None |
| Summary | Python Control Systems Library |
| upload_time | 2024-03-31 17:18:34 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | BSD-3-Clause |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
|
.. image:: https://anaconda.org/conda-forge/control/badges/version.svg
:target: https://anaconda.org/conda-forge/control
.. image:: https://img.shields.io/pypi/v/control.svg
:target: https://pypi.org/project/control/
.. image:: https://github.com/python-control/python-control/actions/workflows/python-package-conda.yml/badge.svg
:target: https://github.com/python-control/python-control/actions/workflows/python-package-conda.yml
.. image:: https://github.com/python-control/python-control/actions/workflows/install_examples.yml/badge.svg
:target: https://github.com/python-control/python-control/actions/workflows/install_examples.yml
.. image:: https://github.com/python-control/python-control/actions/workflows/control-slycot-src.yml/badge.svg
:target: https://github.com/python-control/python-control/actions/workflows/control-slycot-src.yml
.. image:: https://coveralls.io/repos/python-control/python-control/badge.svg
:target: https://coveralls.io/r/python-control/python-control
Python Control Systems Library
==============================
The Python Control Systems Library is a Python module that implements basic
operations for analysis and design of feedback control systems.
Have a go now!
--------------
Try out the examples in the examples folder using the binder service.
.. image:: https://mybinder.org/badge_logo.svg
:target: https://mybinder.org/v2/gh/python-control/python-control/HEAD
The package can also be installed on Google Colab using the commands::
!pip install control
import control as ct
Features
--------
- Linear input/output systems in state-space and frequency domain
- Block diagram algebra: serial, parallel, feedback, and other interconnections
- Time response: initial, step, impulse
- Frequency response: Bode, Nyquist, and Nichols plots
- Control analysis: stability, reachability, observability, stability margins, root locus
- Control design: eigenvalue placement, linear quadratic regulator, sisotool, hinfsyn, rootlocus_pid_designer
- Estimator design: linear quadratic estimator (Kalman filter)
- Nonlinear systems: optimization-based control, describing functions, differential flatness
Links
-----
- Project home page: http://python-control.org
- Source code repository: https://github.com/python-control/python-control
- Documentation: http://python-control.readthedocs.org/
- Issue tracker: https://github.com/python-control/python-control/issues
- Mailing list: http://sourceforge.net/p/python-control/mailman/
Dependencies
------------
The package requires numpy, scipy, and matplotlib. In addition, some routines
use a module called slycot, that is a Python wrapper around some FORTRAN
routines. Many parts of python-control will work without slycot, but some
functionality is limited or absent, and installation of slycot is recommended
(see below). The Slycot wrapper can be found at:
https://github.com/python-control/Slycot
Installation
============
Conda and conda-forge
---------------------
The easiest way to get started with the Control Systems library is
using `Conda <https://conda.io>`_.
The Control Systems library has packages available using the `conda-forge
<https://conda-forge.org>`_ Conda channel, and as of Slycot version
0.3.4, binaries for that package are available for 64-bit Windows,
OSX, and Linux.
To install both the Control Systems library and Slycot in an existing
conda environment, run::
conda install -c conda-forge control slycot
Mixing packages from conda-forge and the default conda channel can
sometimes cause problems with dependencies, so it is usually best to
instally NumPy, SciPy, and Matplotlib from conda-forge as well.
Pip
---
To install using pip::
pip install slycot # optional; see below
pip install control
If you install Slycot using pip you'll need a development environment
(e.g., Python development files, C and Fortran compilers). Pip
installation can be particularly complicated for Windows.
Installing from source
----------------------
To install from source, get the source code of the desired branch or release
from the github repository or archive, unpack, and run from within the
toplevel `python-control` directory::
pip install .
Article and Citation Information
================================
An `article <https://ieeexplore.ieee.org/abstract/document/9683368>`_ about
the library is available on IEEE Explore. If the Python Control Systems Library helped you in your research, please cite::
@inproceedings{python-control2021,
title={The Python Control Systems Library (python-control)},
author={Fuller, Sawyer and Greiner, Ben and Moore, Jason and
Murray, Richard and van Paassen, Ren{\'e} and Yorke, Rory},
booktitle={60th IEEE Conference on Decision and Control (CDC)},
pages={4875--4881},
year={2021},
organization={IEEE}
}
or the GitHub site: https://github.com/python-control/python-control
Development
===========
Code
----
You can check out the latest version of the source code with the command::
git clone https://github.com/python-control/python-control.git
Testing
-------
You can run the unit tests with `pytest`_ to make sure that everything is
working correctly. Inside the source directory, run::
pytest -v
or to test the installed package::
pytest --pyargs control -v
.. _pytest: https://docs.pytest.org/
License
-------
This is free software released under the terms of `the BSD 3-Clause
License <http://opensource.org/licenses/BSD-3-Clause>`_. There is no
warranty; not even for merchantability or fitness for a particular
purpose. Consult LICENSE for copying conditions.
When code is modified or re-distributed, the LICENSE file should
accompany the code or any subset of it, however small. As an
alternative, the LICENSE text can be copied within files, if so
desired.
Contributing
------------
Your contributions are welcome! Simply fork the GitHub repository and send a
`pull request`_.
.. _pull request: https://github.com/python-control/python-control/pulls
Please see the `Developer's Wiki`_ for detailed instructions.
.. _Developer's Wiki: https://github.com/python-control/python-control/wiki
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"description": ".. image:: https://anaconda.org/conda-forge/control/badges/version.svg\n :target: https://anaconda.org/conda-forge/control\n\n.. image:: https://img.shields.io/pypi/v/control.svg\n \u00a0 :target: https://pypi.org/project/control/\n\n.. image:: https://github.com/python-control/python-control/actions/workflows/python-package-conda.yml/badge.svg\n :target: https://github.com/python-control/python-control/actions/workflows/python-package-conda.yml\n\n.. image:: https://github.com/python-control/python-control/actions/workflows/install_examples.yml/badge.svg\n :target: https://github.com/python-control/python-control/actions/workflows/install_examples.yml\n\n.. image:: https://github.com/python-control/python-control/actions/workflows/control-slycot-src.yml/badge.svg\n :target: https://github.com/python-control/python-control/actions/workflows/control-slycot-src.yml\n\n.. image:: https://coveralls.io/repos/python-control/python-control/badge.svg\n :target: https://coveralls.io/r/python-control/python-control\n\nPython Control Systems Library\n==============================\n\nThe Python Control Systems Library is a Python module that implements basic\noperations for analysis and design of feedback control systems.\n\nHave a go now!\n--------------\nTry out the examples in the examples folder using the binder service.\n\n.. image:: https://mybinder.org/badge_logo.svg\n :target: https://mybinder.org/v2/gh/python-control/python-control/HEAD\n\nThe package can also be installed on Google Colab using the commands::\n\n !pip install control\n import control as ct\n\nFeatures\n--------\n\n- Linear input/output systems in state-space and frequency domain\n- Block diagram algebra: serial, parallel, feedback, and other interconnections\n- Time response: initial, step, impulse\n- Frequency response: Bode, Nyquist, and Nichols plots\n- Control analysis: stability, reachability, observability, stability margins, root locus\n- Control design: eigenvalue placement, linear quadratic regulator, sisotool, hinfsyn, rootlocus_pid_designer\n- Estimator design: linear quadratic estimator (Kalman filter)\n- Nonlinear systems: optimization-based control, describing functions, differential flatness\n\nLinks\n-----\n\n- Project home page: http://python-control.org\n- Source code repository: https://github.com/python-control/python-control\n- Documentation: http://python-control.readthedocs.org/\n- Issue tracker: https://github.com/python-control/python-control/issues\n- Mailing list: http://sourceforge.net/p/python-control/mailman/\n\nDependencies\n------------\n\nThe package requires numpy, scipy, and matplotlib. In addition, some routines\nuse a module called slycot, that is a Python wrapper around some FORTRAN\nroutines. Many parts of python-control will work without slycot, but some\nfunctionality is limited or absent, and installation of slycot is recommended\n(see below). 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Pip\ninstallation can be particularly complicated for Windows.\n\nInstalling from source\n----------------------\n\nTo install from source, get the source code of the desired branch or release\nfrom the github repository or archive, unpack, and run from within the\ntoplevel `python-control` directory::\n\n pip install .\n \nArticle and Citation Information\n================================\n\nAn `article <https://ieeexplore.ieee.org/abstract/document/9683368>`_ about\nthe library is available on IEEE Explore. If the Python Control Systems Library helped you in your research, please cite::\n\n @inproceedings{python-control2021,\n title={The Python Control Systems Library (python-control)},\n author={Fuller, Sawyer and Greiner, Ben and Moore, Jason and\n Murray, Richard and van Paassen, Ren{\\'e} and Yorke, Rory},\n booktitle={60th IEEE Conference on Decision and Control (CDC)},\n pages={4875--4881},\n year={2021},\n organization={IEEE}\n }\n\nor the GitHub site: https://github.com/python-control/python-control\n\n\nDevelopment\n===========\n\nCode\n----\n\nYou can check out the latest version of the source code with the command::\n\n git clone https://github.com/python-control/python-control.git\n\nTesting\n-------\n\nYou can run the unit tests with `pytest`_ to make sure that everything is\nworking correctly. 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