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Initial support for discrete time systems (version 0.6)
 * Added dt class variable to keep track of whether system is discrete * Algebraic operations check for timebase consistency * Functions that don't support discrete time generate NotImplementedError * Added unit tests for code that has been implemented so far * Updated version number to 0.6a
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‎ChangeLog

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2012-10-06 Richard Murray <murray@altura.local>
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* src/dtime.py: new module with functions for operating on discrete
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time systems
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* src/modelsimp.py: added NotImplementedError for discrete time
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* src/freqplot.py: added NotImplementedError for discrete time
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* src/bdalg.py: added documentation about timebases (discrete versus
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continuous)
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* src/statesp.py (_mimo2siso): include sampling time
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* src/xferfcn.py (TransferFunction.__str__): added optional var
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keyword to allow any symbol to be used
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* src/matlab.py (tf2ss): added code required to keep track of dt
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* src/xferfcn.py (TransferFunction.__str__): added additional string for
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discrete time system, plus use 'z' for polynomial variable
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(TransferFunction.__neg__): set sampling time for negation
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(TransferFunction.__add__): added test for same sampling time
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(TransferFunction.__mul__): added test for same sampling time
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(TransferFunction.__div__): added test for same sampling time
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(TransferFunction.feedback): added test for same sampling time
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* src/statesp.py (StateSpace.__str__): added additional string for
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discrete time system
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(StateSpace.__add__): added test for same sampling time
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(StateSpace.__mul__): added test for same sampling time
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(StateSpace.__rmul__): set sampling time for product
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(StateSpace.__neg__): set sampling time for negation
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(StateSpace.feedback): added test for same sampling time
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* tests/discrete_test.py (TestDiscrete): unit tests for discrete
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time systems
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* src/xferfcn.py (TransferFunction.__init__): added dt class
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variable for discrete time systems
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* src/statesp.py (StateSpace.__init__): added dt class variable for
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discrete time systems
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---- control-0.5c released -----
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2012-10-03 Richard Murray <murray@altura.local>
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* tests/matlab_test.py (TestMatlab.testSsdata): unit test

‎doc/conf.py

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# built documents.
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#
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# The short X.Y version.
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version = '0.5c'
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version = '0.6'
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# The full version, including alpha/beta/rc tags.
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release = '0.5c'
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release = '0.6c'
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# The language for content autogenerated by Sphinx. Refer to documentation
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# for a list of supported languages.

‎setup.py

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from setuptools import setup
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setup(name = 'control',
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version = '0.5c',
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version = '0.6a',
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description = 'Python Control Systems Library',
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author = 'Richard Murray',
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author_email = 'murray@cds.caltech.edu',

‎src/__init__.py

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#! Should probably only import the exact functions we use...
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from bdalg import series, parallel, negate, feedback
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from delay import pade
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from dtime import timebase, isdtime, isctime
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from freqplot import bode_plot, nyquist_plot, gangof4_plot
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from freqplot import bode, nyquist, gangof4
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from margins import stability_margins, phase_crossover_frequencies

‎src/bdalg.py

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@@ -71,6 +71,7 @@ def series(sys1, sys2):
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------
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ValueError
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if `sys2.inputs` does not equal `sys1.outputs`
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if `sys1.dt` is not compatible with `sys2.dt`
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See Also
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--------
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TransferFunction classes. The output type is usually the type of `sys2`.
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If `sys2` is a scalar, then the output type is the type of `sys1`.
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If both systems have a defined timebase (dt = 0 for continuous time,
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dt > 0 for discrete time), then the timebase for both systems much
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match. If only one of the system has a timebase, the return
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timebase will be set to match it.
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Examples
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--------
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>>> sys3 = series(sys1, sys2) # Same as sys3 = sys2 * sys1.
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Notes
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-----
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This function is a wrapper for the __add__ function in the StateSpace and
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TransferFunction classes. The output type is usually the type of `sys1`. If
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`sys1` is a scalar, then the output type is the type of `sys2`.
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This function is a wrapper for the __add__ function in the
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StateSpace and TransferFunction classes. The output type is usually
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the type of `sys1`. If `sys1` is a scalar, then the output type is
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the type of `sys2`.
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If both systems have a defined timebase (dt = 0 for continuous time,
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dt > 0 for discrete time), then the timebase for both systems much
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match. If only one of the system has a timebase, the return
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timebase will be set to match it.
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Examples
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--------
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This function is a wrapper for the __neg__ function in the StateSpace and
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TransferFunction classes. The output type is the same as the input type.
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If both systems have a defined timebase (dt = 0 for continuous time,
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dt > 0 for discrete time), then the timebase for both systems much
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match. If only one of the system has a timebase, the return
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timebase will be set to match it.
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Examples
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--------
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>>> sys2 = negate(sys1) # Same as sys2 = -sys1.

‎src/dtime.py

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"""dtime.py
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Utility functions for disrete time systems.
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Routines in this module:
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isdtime()
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isctime()
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timebase()
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"""
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"""Copyright (c) 2012 by California Institute of Technology
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions
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are met:
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1. Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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3. Neither the name of the California Institute of Technology nor
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the names of its contributors may be used to endorse or promote
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products derived from this software without specific prior
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written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL CALTECH
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OR THE CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
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USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
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OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
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SUCH DAMAGE.
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Author: Richard M. Murray
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Date: 6 October 2012
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$Id: dtime.py 185 2012-08-30 05:44:32Z murrayrm $
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"""
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from statesp import StateSpace
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from xferfcn import TransferFunction
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# Return the timebase of a system
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def timebase(sys):
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# TODO: add docstring
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# If we get passed a constant, timebase is None
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if isinstance(sys, (int, float, long, complex)):
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return None
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# Check for a transfer fucntion or state space object
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if isinstance(sys, (StateSpace, TransferFunction)):
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if sys.dt > 0:
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return 'dtime';
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elif sys.dt == 0:
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return 'ctime';
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elif sys.dt == None:
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return None
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# Got pased something we don't recognize or bad timebase
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return False;
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# Check to see if a system is a discrete time system
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def isdtime(sys, strict=False):
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# TODO: add docstring
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# Check to see if this is a constant
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if isinstance(sys, (int, float, long, complex)):
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# OK as long as strict checking is off
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return True if not strict else False
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# Check for a transfer fucntion or state space object
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if isinstance(sys, (StateSpace, TransferFunction)):
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# Look for dt > 0 or dt == None (if not strict)
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return sys.dt > 0 or (not strict and sys.dt == None)
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# Got possed something we don't recognize
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return False
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# Check to see if a system is a continuous time system
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def isctime(sys, strict=False):
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# TODO: add docstring
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# Check to see if this is a constant
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if isinstance(sys, (int, float, long, complex)):
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# OK as long as strict checking is off
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return True if not strict else False
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# Check for a transfer fucntion or state space object
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if isinstance(sys, (StateSpace, TransferFunction)):
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# Look for dt == 0 or dt == None (if not strict)
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return sys.dt == 0 or (not strict and sys.dt == None)
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# Got possed something we don't recognize
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return False
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‎src/freqplot.py

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import numpy as np
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from ctrlutil import unwrap
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from bdalg import feedback
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from dtime import isdtime
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#
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# Main plotting functions
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mags, phases, omegas = [], [], []
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for sys in syslist:
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# TODO: implement for discrete time systems
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if (isdtime(sys, strict=True)):
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raise(NotImplementedError("Function not implemented in discrete time"))
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if (sys.inputs > 1 or sys.outputs > 1):
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#TODO: Add MIMO bode plots.
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raise NotImplementedError("Bode is currently only implemented for SISO systems.")
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omega = np.logspace(np.log10(omega[0]), np.log10(omega[1]),
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num=50, endpoint=True, base=10.0)
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for sys in syslist:
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# TODO: implement for discrete time systems
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if (isdtime(sys, strict=True)):
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raise(NotImplementedError("Function not implemented in discrete time"))
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if (sys.inputs > 1 or sys.outputs > 1):
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#TODO: Add MIMO nyquist plots.
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raise NotImplementedError("Nyquist is currently only implemented for SISO systems.")
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-------
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None
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"""
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# TODO: implement for discrete time systems
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if (isdtime(P, strict=True) or isdtime(C, strict=True)):
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raise(NotImplementedError("Function not implemented in discrete time"))
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if (P.inputs > 1 or P.outputs > 1 or C.inputs > 1 or C.outputs >1):
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#TODO: Add MIMO go4 plots.
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raise NotImplementedError("Gang of four is currently only implemented for SISO systems.")
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if (not getattr(syslist, '__iter__', False)):
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syslist = (syslist,)
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for sys in syslist:
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# TODO: implement for discrete time systems
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if (isdtime(sys, strict=True)):
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raise(NotImplementedError("Function not implemented in discrete time"))
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# Add new features to the list
357374
features = np.concatenate((features, np.abs(sys.pole())))
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features = np.concatenate((features, np.abs(sys.zero())))

‎src/margins.py

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import xferfcn
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from freqplot import bode
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import numpy as np
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from dtime import isdtime
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# gain and phase margins
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# contributed by Sawyer B. Fuller <minster@caltech.edu>
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8990
if (not getattr(sysdata, '__iter__', False)):
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sys = sysdata
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# TODO: implement for discrete time systems
94+
if (isdtime(sys, strict=True)):
95+
raise(NotImplementedError("Function not implemented in discrete time"))
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9197
mag, phase, omega = bode(sys, deg=deg, Plot=False)
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elif len(sysdata) == 3:
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# TODO: replace with FRD object type?
93100
mag, phase, omega = sysdata
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else:
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raise ValueError("Margin sysdata must be either a linear system or a 3-sequence of mag, phase, omega.")

‎src/matlab.py

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"""
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616-
if len(args) == 4:
617-
# Assume we were given the A, B, C, D matrix
618-
return _convertToTransferFunction(StateSpace(args[0], args[1], args[2],
619-
args[3]))
616+
if len(args) == 4 or len(args) == 5:
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# Assume we were given the A, B, C, D matrix and (optional) dt
618+
return _convertToTransferFunction(StateSpace(*args))
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620620
elif len(args) == 1:
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sys = args[0]
622622
if isinstance(sys, StateSpace):
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684684
"""
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686-
if len(args) == 2:
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if len(args) == 2 or len(args) == 3:
687687
# Assume we were given the num, den
688-
return _convertToStateSpace(TransferFunction(args[0], args[1]))
688+
return _convertToStateSpace(TransferFunction(*args))
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elif len(args) == 1:
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sys = args[0]
691692
if not isinstance(sys, TransferFunction):

‎src/modelsimp.py

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from exception import *
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from statefbk import *
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from statesp import StateSpace
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from dtime import isdtime, isctime
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# Hankel Singular Value Decomposition
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# The following returns the Hankel singular values, which are singular values
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>>> H = hsvd(sys)
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"""
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# TODO: implement for discrete time systems
85+
if (isdtime(sys, strict=True)):
86+
raise(NotImplementedError("Function not implemented in discrete time"))
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Wc = gram(sys,'c')
8489
Wo = gram(sys,'o')
8590
WoWc = np.dot(Wo, Wc)
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132137
# elif isDisc():
133138
# dico = 'D'
134139
# else:
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dico = 'C'
140+
if (isctime(sys)):
141+
dico = 'C'
142+
else:
143+
raise(NotImplementedError("Function not implemented in discrete time"))
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137146
#Check system is stable
138147
D,V = np.linalg.eig(sys.A)

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