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.gitignore

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.coverage
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doc/_build
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doc/generated
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examples/.ipynb_checkpoints/
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.ipynb_checkpoints/
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.settings/org.eclipse.core.resources.prefs
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.pydevproject
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.project

README.rst

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The package can also be installed on Google Colab using the commands::
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!pip install control
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%pip install control
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import control as ct
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Features
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Links
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-----
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- Project home page: http://python-control.org
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- Project home page: https://python-control.org
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- Source code repository: https://github.com/python-control/python-control
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- Documentation: http://python-control.readthedocs.org/
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- Documentation: https://python-control.readthedocs.io/
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- Issue tracker: https://github.com/python-control/python-control/issues
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- Mailing list: http://sourceforge.net/p/python-control/mailman/
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- Mailing list: https://sourceforge.net/p/python-control/mailman/
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Dependencies
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------------
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-------
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This is free software released under the terms of `the BSD 3-Clause
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License <http://opensource.org/licenses/BSD-3-Clause>`_. There is no
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License <https://opensource.org/licenses/BSD-3-Clause>`_. There is no
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warranty; not even for merchantability or fitness for a particular
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purpose. Consult LICENSE for copying conditions.
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control/__init__.py

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The initial goal for the package is to implement all of the
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functionality required to work through the examples in the textbook
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`Feedback Systems <http://fbsbook.org>`_ by Astrom and Murray. In
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`Feedback Systems <https://fbsbook.org>`_ by Astrom and Murray. In
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addition to standard techniques available for linear control systems,
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support for nonlinear systems (including trajectory generation, gain
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scheduling, phase plane diagrams, and describing functions) is

control/config.py

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def use_fbs_defaults():
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"""Use Feedback Systems (FBS) compatible settings.
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The following conventions from `Feedback Systems <http://fbsbook.org>`_
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The following conventions from `Feedback Systems <https://fbsbook.org>`_
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are used:
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* Bode plots plot gain in powers of ten, phase in degrees,

control/freqplot.py

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#
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# Because plots can be built up by multiple calls to plot(), the legend
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# strings are created from the line labels manually. Thus an initial
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# call to plot() may not generate any legends (eg, if no signals are
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# call to plot() may not generate any legends (e.g., if no signals are
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# overlaid), but subsequent calls to plot() will need a legend for each
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# different response (system).
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#

control/modelsimp.py

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.. [1] J.-N. Juang, M. Phan, L. G. Horta, and R. W. Longman,
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Identification of observer/Kalman filter Markov parameters - Theory
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and experiments. Journal of Guidance Control and Dynamics, 16(2),
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320-329, 2012. http://doi.org/10.2514/3.21006
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320-329, 2012. https://doi.org/10.2514/3.21006
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Examples
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--------
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# J.-N. Juang, M. Phan, L. G. Horta, and R. W. Longman, Identification
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# of observer/Kalman filter Markov parameters - Theory and
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# experiments. Journal of Guidance Control and Dynamics, 16(2),
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# 320-329, 2012. http://doi.org/10.2514/3.21006
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# 320-329, 2012. https://doi.org/10.2514/3.21006
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#
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# Set up the full problem

control/statefbk.py

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ctrl, clsys = ct.create_statefbk_iosystem(sys, K)
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where `sys` is the process dynamics and `K` is the state (+ integral)
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feedback gain (eg, from LQR). The function returns the controller
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feedback gain (e.g., from LQR). The function returns the controller
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`ctrl` and the closed loop systems `clsys`, both as I/O systems.
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A gain scheduled controller can also be created, by passing a list of

control/statesp.py

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warn("state labels specified for "
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"non-unique state space realization")
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# Allow method to be specified (eg, tf2ss)
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# Allow method to be specified (e.g., tf2ss)
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method = kwargs.pop('method', None)
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# Create a state space system from an LTI system

control/timeplot.py

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# Because plots can be built up by multiple calls to plot(), the legend
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# strings are created from the line labels manually. Thus an initial
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# call to plot() may not generate any legends (eg, if no signals are
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# call to plot() may not generate any legends (e.g., if no signals are
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# combined nor overlaid), but subsequent calls to plot() will need a
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# legend for each different line (system).
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#

control/timeresp.py

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# We can't put the impulse into U because there is no numerical
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# representation for it (infinitesimally short, infinitely high).
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# See also: http://www.mathworks.com/support/tech-notes/1900/1901.html
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# See also: https://www.mathworks.com/support/tech-notes/1900/1901.html
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#
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if isctime(sys):
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X0 = sys.B[:, i]

doc/develop.rst

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The python-control package is maintained on GitHub, with documentation
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hosted by ReadTheDocs and a mailing list on SourceForge:
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* Project home page: http://python-control.org
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* Project home page: https://python-control.org
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* Source code repository: https://github.com/python-control/python-control
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* Documentation: http://python-control.readthedocs.org/
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* Documentation: https://python-control.readthedocs.io/
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* Issue tracker: https://github.com/python-control/python-control/issues
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* Mailing list: http://sourceforge.net/p/python-control/mailman/
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* Mailing list: https://sourceforge.net/p/python-control/mailman/
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GitHub repository file and directory layout:
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- **python-control/** - main repository
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+ **matlab/** - MATLAB compatibility subpackage
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- __init.py, timeresp.py, wrappers.py - subpackage files
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- __init__.py, timeresp.py, wrappers.py - subpackage files
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+ **tests/** - unit tests
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timepts, outputs, states=states, inputs=inputs)
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In the last command, note that states precedes inputs because not
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all TimeResponseData elements have inputs (eg, `initial_response`).
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all TimeResponseData elements have inputs (e.g., `initial_response`).
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* The default order for providing arguments in the frequency domain is
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system/response first, then frequency::
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- The Python built-ins occur frequently and are capitalized, and so
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the additional formatting doesn't add much and would be
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inconsistent if you jump from the User Guide to the Reference
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Manual (eg, to look at a function more closely via a link in the
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Manual (e.g., to look at a function more closely via a link in the
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doc/examples/template.py

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def sample_method(self, data):
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"""Sample method within a class.
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This is an example of a method within a class. Document using
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updating `__init__.py` to import the function (often by importing the
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entire module).
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Docstring should be in standard numpy doc format. The extended summary
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Docstring should be in standard numpydoc format. The extended summary
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(this text) should describe the basic operation of the function, with
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technical details in the "Notes" section.
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doc/index.rst

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- GitHub repository: https://github.com/python-control/python-control
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- Issue tracker: https://github.com/python-control/python-control/issues
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- Mailing list: http://sourceforge.net/p/python-control/mailman/
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- Mailing list: https://sourceforge.net/p/python-control/mailman/
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.. rubric:: How to cite
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doc/intro.rst

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Users familiar with the MATLAB control systems toolbox will find much
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of the functionality implemented in `python-control`, though using
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Python constructs and coding conventions. The python-control package
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makes heavy use of `NumPy <http://www.numpy.org>`_ and `SciPy
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makes heavy use of `NumPy <https://www.numpy.org>`_ and `SciPy
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<https://www.scipy.org>`_ and many differences are reflected in the
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use of those . A list of general differences between NumPy and MATLAB
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can be found `here

doc/iosys.rst

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To illustrate the use of the :func:`interconnect` function, we create a
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<https://fbsbook.org>`_, Example 7.5):
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`Feedback Systems <https://fbsbook.org>`_, Section 7.2 (Stabilization
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doc/releases/0.10.0-notes.rst

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* `phase_plot`: Use `phase_plane_plot` instead.
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doc/releases/0.10.1-notes.rst

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the next major or minor version update).

doc/releases/0.9.3-notes.rst

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the next major or minor version update).

doc/releases/0.9.4-notes.rst

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doc/releases/template.rst

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examples/.gitignore

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.ipynb-clean
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