addressed @slivingston review comments

Author: murrayrm

.gitignore

@@ -14,7 +14,7 @@ record.txt
 .coverage
 doc/_build
 doc/generated
-examples/.ipynb_checkpoints/
+.ipynb_checkpoints/
 .settings/org.eclipse.core.resources.prefs
 .pydevproject
 .project

README.rst

@@ -31,7 +31,7 @@ Try out the examples in the examples folder using the binder service.
 
 The package can also be installed on Google Colab using the commands::
 
-  !pip install control
+  %pip install control
   import control as ct
 
 Features
@@ -49,11 +49,11 @@ Features
 Links
 -----
 
-- Project home page: http://python-control.org
+- Project home page: https://python-control.org
 - Source code repository: https://github.com/python-control/python-control
-- Documentation: http://python-control.readthedocs.org/
+- Documentation: https://python-control.readthedocs.io/
 - Issue tracker: https://github.com/python-control/python-control/issues
-- Mailing list: http://sourceforge.net/p/python-control/mailman/
+- Mailing list: https://sourceforge.net/p/python-control/mailman/
 
 Dependencies
 ------------
@@ -158,7 +158,7 @@ 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
+License <https://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.
 

control/__init__.py

@@ -9,7 +9,7 @@
 
 The initial goal for the package is to implement all of the
 functionality required to work through the examples in the textbook
-`Feedback Systems <http://fbsbook.org>`_ by Astrom and Murray.  In
+`Feedback Systems <https://fbsbook.org>`_ by Astrom and Murray.  In
 addition to standard techniques available for linear control systems,
 support for nonlinear systems (including trajectory generation, gain
 scheduling, phase plane diagrams, and describing functions) is

control/config.py

@@ -272,7 +272,7 @@ def use_matlab_defaults():
 def use_fbs_defaults():
     """Use Feedback Systems (FBS) compatible settings.
 
-    The following conventions from `Feedback Systems <http://fbsbook.org>`_
+    The following conventions from `Feedback Systems <https://fbsbook.org>`_
     are used:
 
         * Bode plots plot gain in powers of ten, phase in degrees,

control/freqplot.py

@@ -1033,7 +1033,7 @@ def gen_zero_centered_series(val_min, val_max, period):
     #
     # Because plots can be built up by multiple calls to plot(), the legend
     # strings are created from the line labels manually.  Thus an initial
-    # call to plot() may not generate any legends (eg, if no signals are
+    # call to plot() may not generate any legends (e.g., if no signals are
     # overlaid), but subsequent calls to plot() will need a legend for each
     # different response (system).
     #

control/modelsimp.py

@@ -598,7 +598,7 @@ def markov(*args, m=None, transpose=False, dt=None, truncate=False):
     .. [1] J.-N. Juang, M. Phan, L. G.  Horta, and R. W. Longman,
        Identification of observer/Kalman filter Markov parameters - Theory
        and experiments. Journal of Guidance Control and Dynamics, 16(2),
-       320-329, 2012. http://doi.org/10.2514/3.21006
+       320-329, 2012. https://doi.org/10.2514/3.21006
 
     Examples
     --------
@@ -696,7 +696,7 @@ def markov(*args, m=None, transpose=False, dt=None, truncate=False):
     #   J.-N. Juang, M. Phan, L. G. Horta, and R. W. Longman, Identification
     #   of observer/Kalman filter Markov parameters - Theory and
     #   experiments. Journal of Guidance Control and Dynamics, 16(2),
-    #   320-329, 2012. http://doi.org/10.2514/3.21006
+    #   320-329, 2012. https://doi.org/10.2514/3.21006
     #
 
     # Set up the full problem

control/statefbk.py

@@ -567,7 +567,7 @@ def create_statefbk_iosystem(
         ctrl, clsys = ct.create_statefbk_iosystem(sys, K)
 
     where `sys` is the process dynamics and `K` is the state (+ integral)
-    feedback gain (eg, from LQR).  The function returns the controller
+    feedback gain (e.g., from LQR).  The function returns the controller
     `ctrl` and the closed loop systems `clsys`, both as I/O systems.
 
     A gain scheduled controller can also be created, by passing a list of

control/statesp.py

@@ -1760,7 +1760,7 @@ def ss(*args, **kwargs):
                 warn("state labels specified for "
                      "non-unique state space realization")
 
-            # Allow method to be specified (eg, tf2ss)
+            # Allow method to be specified (e.g., tf2ss)
             method = kwargs.pop('method', None)
 
             # Create a state space system from an LTI system

control/timeplot.py

@@ -576,7 +576,7 @@ def _make_line_label(signal_index, signal_labels, trace_index):
     #
     # Because plots can be built up by multiple calls to plot(), the legend
     # strings are created from the line labels manually.  Thus an initial
-    # call to plot() may not generate any legends (eg, if no signals are
+    # call to plot() may not generate any legends (e.g., if no signals are
     # combined nor overlaid), but subsequent calls to plot() will need a
     # legend for each different line (system).
     #

control/timeresp.py

@@ -1963,7 +1963,7 @@ def impulse_response(
         #
         # We can't put the impulse into U because there is no numerical
         # representation for it (infinitesimally short, infinitely high).
-        # See also: http://www.mathworks.com/support/tech-notes/1900/1901.html
+        # See also: https://www.mathworks.com/support/tech-notes/1900/1901.html
         #
         if isctime(sys):
             X0 = sys.B[:, i]