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Improved default time vector and handling for time response functions step, impulse, and initial#420

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Merged
murrayrm merged 11 commits intopython-control:masterfromsawyerbfuller:fix-discrete-step-response
Jul 11, 2020
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b39184b
fixed default response time for time response of discrete-time functi…
sawyerbfullerJun 18, 2020
32b610b
to pass tests, added convenient ability to specify simulation time an…
sawyerbfullerJun 19, 2020
9a8da65
eliminated deprecation warnings by importing certain functions from n…
sawyerbfullerJun 19, 2020
db9f197
eliminated deprecation warnings by importing certain functions from n…
sawyerbfullerJun 19, 2020
6d62910
small fix to pass unit tests
sawyerbfullerJun 19, 2020
9f02119
adjusted sisotool test so tests pass with new default step response t…
sawyerbfullerJun 19, 2020
1bc60ba
added functionality to automatically choose dt in timeresp.py based o…
sawyerbfullerJun 21, 2020
512f822
removed some leftover code and comments
sawyerbfullerJun 21, 2020
79951a1
explanation in docstrings for how time vector T is auto-computed in t…
sawyerbfullerJun 28, 2020
5a34fc0
Merge branch 'master' into fix-discrete-step-response
murrayrmJul 11, 2020
e155a15
fix unit test precision in sisotool_test.py
murrayrmJul 11, 2020
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4 changes: 2 additions & 2 deletionscontrol/freqplot.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -822,10 +822,10 @@ def default_frequency_range(syslist, Hz=None, number_of_samples=None,

# Set the range to be an order of magnitude beyond any features
if number_of_samples:
omega =sp.logspace(
omega =np.logspace(
lsp_min, lsp_max, num=number_of_samples, endpoint=True)
else:
omega =sp.logspace(lsp_min, lsp_max, endpoint=True)
omega =np.logspace(lsp_min, lsp_max, endpoint=True)
return omega


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31 changes: 17 additions & 14 deletionscontrol/matlab/timeresp.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -21,8 +21,9 @@ def step(sys, T=None, X0=0., input=0, output=None, return_x=False):
sys: StateSpace, or TransferFunction
LTI system to simulate

T: array-like object, optional
Time vector (argument is autocomputed if not given)
T: array-like or number, optional
Time vector, or simulation time duration if a number (time vector is
autocomputed if not given)

X0: array-like or number, optional
Initial condition (default = 0)
Expand DownExpand Up@@ -59,7 +60,7 @@ def step(sys, T=None, X0=0., input=0, output=None, return_x=False):
from ..timeresp import step_response

T, yout, xout = step_response(sys, T, X0, input, output,
transpose =True, return_x=True)
transpose=True, return_x=True)

if return_x:
return yout, T, xout
Expand All@@ -75,8 +76,9 @@ def stepinfo(sys, T=None, SettlingTimeThreshold=0.02, RiseTimeLimits=(0.1,0.9)):
sys: StateSpace, or TransferFunction
LTI system to simulate

T: array-like object, optional
Time vector (argument is autocomputed if not given)
T: array-like or number, optional
Time vector, or simulation time duration if a number (time vector is
autocomputed if not given)

SettlingTimeThreshold: float value, optional
Defines the error to compute settling time (default = 0.02)
Expand DownExpand Up@@ -127,9 +129,10 @@ def impulse(sys, T=None, X0=0., input=0, output=None, return_x=False):
sys: StateSpace, TransferFunction
LTI system to simulate

T: array-like object, optional
Time vector (argument is autocomputed if not given)

T: array-like or number, optional
Time vector, or simulation time duration if a number (time vector is
autocomputed if not given)

X0: array-like or number, optional
Initial condition (default = 0)

Expand DownExpand Up@@ -182,9 +185,10 @@ def initial(sys, T=None, X0=0., input=None, output=None, return_x=False):
sys: StateSpace, or TransferFunction
LTI system to simulate

T: array-like object, optional
Time vector (argument is autocomputed if not given)

T: array-like or number, optional
Time vector, or simulation time duration if a number (time vector is
autocomputed if not given)

X0: array-like object or number, optional
Initial condition (default = 0)

Expand DownExpand Up@@ -245,9 +249,8 @@ def lsim(sys, U=0., T=None, X0=0.):
If `U` is ``None`` or ``0``, a special algorithm is used. This special
algorithm is faster than the general algorithm, which is used otherwise.

T: array-like
Time steps at which the input is defined, numbers must be (strictly
monotonic) increasing.
T: array-like, optional for discrete LTI `sys`
Time steps at which the input is defined; values must be evenly spaced.

X0: array-like or number, optional
Initial condition (default = 0).
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2 changes: 1 addition & 1 deletioncontrol/rlocus.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -50,7 +50,7 @@
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
fromscipy import array, poly1d, row_stack, zeros_like, real, imag
fromnumpy import array, poly1d, row_stack, zeros_like, real, imag
import scipy.signal # signal processing toolbox
import pylab # plotting routines
from .xferfcn import _convert_to_transfer_function
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2 changes: 1 addition & 1 deletioncontrol/sisotool.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -136,7 +136,7 @@ def _SisotoolUpdate(sys,fig,K,bode_plot_params,tvect=None):
# Generate the step response and plot it
sys_closed = (K*sys).feedback(1)
if tvect is None:
tvect, yout = step_response(sys_closed)
tvect, yout = step_response(sys_closed, T_num=100)
else:
tvect, yout = step_response(sys_closed,tvect)
ax_step.plot(tvect, yout)
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16 changes: 8 additions & 8 deletionscontrol/tests/sisotool_test.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -33,10 +33,10 @@ def test_sisotool(self):

# Check the step response before moving the point
step_response_original = np.array(
[0., 0.02233651, 0.13118374, 0.33078542, 0.5907113, 0.87041549,
1.13038536, 1.33851053, 1.47374666, 1.52757114])
assert_array_almost_equal(ax_step.lines[0].get_data()[1][:10],
step_response_original, 4)
[0., 0.0217, 0.1281, 0.3237, 0.5797, 0.8566, 1.116,
1.3261, 1.4659, 1.526])
assert_array_almost_equal(
ax_step.lines[0].get_data()[1][:10], step_response_original, 4)

bode_plot_params = {
'omega': None,
Expand DownExpand Up@@ -78,10 +78,10 @@ def test_sisotool(self):

# Check if the step response has changed
step_response_moved = np.array(
[0., 0.02458187, 0.16529784, 0.46602716, 0.91012035, 1.43364313,
1.93996334, 2.3190105, 2.47041552, 2.32724853])
assert_array_almost_equal(ax_step.lines[0].get_data()[1][:10],
step_response_moved, 4)
[0., 0.0239, 0.161, 0.4547, 0.8903, 1.407,
1.9121, 2.2989, 2.4686, 2.353])
assert_array_almost_equal(
ax_step.lines[0].get_data()[1][:10], step_response_moved, 4)


if __name__ == "__main__":
Expand Down
71 changes: 69 additions & 2 deletionscontrol/tests/timeresp_test.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -11,6 +11,7 @@
import unittest
import numpy as np
from control.timeresp import *
from control.timeresp import _ideal_tfinal_and_dt, _default_time_vector
from control.statesp import *
from control.xferfcn import TransferFunction, _convert_to_transfer_function
from control.dtime import c2d
Expand DownExpand Up@@ -94,6 +95,7 @@ def test_step_response(self):
np.testing.assert_array_equal(Tc.shape, Td.shape)
np.testing.assert_array_equal(youtc.shape, youtd.shape)


# Recreate issue #374 ("Bug in step_response()")
def test_step_nostates(self):
# Continuous time, constant system
Expand DownExpand Up@@ -346,10 +348,75 @@ def test_step_robustness(self):
sys2 = TransferFunction(num, den2)

# Compute step response from input 1 to output 1, 2
t1, y1 = step_response(sys1, input=0)
t2, y2 = step_response(sys2, input=0)
t1, y1 = step_response(sys1, input=0, T_num=100)
t2, y2 = step_response(sys2, input=0, T_num=100)
np.testing.assert_array_almost_equal(y1, y2)

def test_auto_generated_time_vector(self):
# confirm a TF with a pole at p simulates for 7.0/p seconds
p = 0.5
np.testing.assert_array_almost_equal(
_ideal_tfinal_and_dt(TransferFunction(1, [1, .5]))[0],
(7/p))
np.testing.assert_array_almost_equal(
_ideal_tfinal_and_dt(TransferFunction(1, [1, .5]).sample(.1))[0],
(7/p))
# confirm a TF with poles at 0 and p simulates for 7.0/p seconds
np.testing.assert_array_almost_equal(
_ideal_tfinal_and_dt(TransferFunction(1, [1, .5, 0]))[0],
(7/p))
# confirm a TF with a natural frequency of wn rad/s gets a
# dt of 1/(7.0*wn)
wn = 10
np.testing.assert_array_almost_equal(
_ideal_tfinal_and_dt(TransferFunction(1, [1, 0, wn**2]))[1],
1/(7.0*wn))
zeta = .1
np.testing.assert_array_almost_equal(
_ideal_tfinal_and_dt(TransferFunction(1, [1, 2*zeta*wn, wn**2]))[1],
1/(7.0*wn))
# but a smapled one keeps its dt
np.testing.assert_array_almost_equal(
_ideal_tfinal_and_dt(TransferFunction(1, [1, 2*zeta*wn, wn**2]).sample(.1))[1],
.1)
np.testing.assert_array_almost_equal(
np.diff(initial_response(TransferFunction(1, [1, 2*zeta*wn, wn**2]).sample(.1))[0][0:2]),
.1)
np.testing.assert_array_almost_equal(
_ideal_tfinal_and_dt(TransferFunction(1, [1, 2*zeta*wn, wn**2]))[1],
1/(7.0*wn))
# TF with fast oscillations simulates only 5000 time steps even with long tfinal
self.assertEqual(5000,
len(_default_time_vector(TransferFunction(1, [1, 0, wn**2]),tfinal=100)))
# and simulates for 7.0/dt time steps
self.assertEqual(
len(_default_time_vector(TransferFunction(1, [1, 0, wn**2]))),
int(7.0/(1/(7.0*wn))))

sys = TransferFunction(1, [1, .5, 0])
sysdt = TransferFunction(1, [1, .5, 0], .1)
# test impose number of time steps
self.assertEqual(10, len(step_response(sys, T_num=10)[0]))
self.assertEqual(10, len(step_response(sysdt, T_num=10)[0]))
# test impose final time
np.testing.assert_array_almost_equal(
100,
step_response(sys, 100)[0][-1],
decimal=.5)
np.testing.assert_array_almost_equal(
100,
step_response(sysdt, 100)[0][-1],
decimal=.5)
np.testing.assert_array_almost_equal(
100,
impulse_response(sys, 100)[0][-1],
decimal=.5)
np.testing.assert_array_almost_equal(
100,
initial_response(sys, 100)[0][-1],
decimal=.5)


def test_time_vector(self):
"Unit test: https://github.com/python-control/python-control/issues/239"
# Discrete time simulations with specified time vectors
Expand Down
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