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josiahdelangejosiahdelange
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Recommended changes from the linter
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3 files changed

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‎control/margins.py

Lines changed: 1 addition & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -10,8 +10,6 @@
1010

1111
import numpy as np
1212
import scipy as sp
13-
import matplotlib
14-
import matplotlib.pyplot as plt
1513

1614
from . import frdata, freqplot, xferfcn, statesp
1715
from .exception import ControlMIMONotImplemented
@@ -631,7 +629,7 @@ def disk_margins(L, omega, skew = 0.0, returnall = False):
631629
if L.issiso() and (ab13md == None):
632630
# For the SISO case, the norm on (S + (skew - I)/2) is
633631
# unstructured, and can be computed as Bode magnitude
634-
DM[ii] = 1.0/bode(ST_jw, omega = omega[ii], plot = False)[0]
632+
DM[ii] = 1.0/ST_mag[ii]
635633
else:
636634
# For the MIMO case, the norm on (S + (skew - I)/2) assumes a
637635
# single complex uncertainty block diagonal uncertainty structure.

‎control/tests/margin_test.py

Lines changed: 0 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -425,9 +425,6 @@ def test_siso_disk_margin_return_all():
425425
# Frequencies of interest
426426
omega = np.logspace(-1, 2, 1001)
427427

428-
# Laplace variable
429-
s = tf('s')
430-
431428
# Loop transfer function
432429
L = tf(25, [1, 10, 10, 10])
433430

@@ -445,9 +442,6 @@ def test_mimo_disk_margin_return_all():
445442
# Frequencies of interest
446443
omega = np.logspace(-1, 3, 1001)
447444

448-
# Laplace variable
449-
s = tf('s')
450-
451445
# Loop transfer gain
452446
P = ss([[0, 10],[-10, 0]], np.eye(2),\
453447
[[1, 10], [-10, 1]], [[0, 0],[0, 0]]) # plant

‎examples/disk_margins.py

Lines changed: 14 additions & 25 deletions
Original file line numberDiff line numberDiff line change
@@ -2,17 +2,12 @@
22
Demonstrate disk-based stability margin calculations.
33
"""
44

5-
import os, sys, math
6-
import numpy as np
7-
import control
8-
5+
import os
96
import math
10-
import matplotlib as mpl
7+
import control
8+
import matplotlib
119
import matplotlib.pyplot as plt
12-
from warnings import warn
13-
1410
import numpy as np
15-
import scipy as sp
1611

1712
def plot_allowable_region(alpha_max, skew, ax = None):
1813
"""Plot region of allowable gain/phase variation, given worst-case disk margin.
@@ -122,19 +117,16 @@ def test_siso1():
122117
# Frequencies of interest
123118
omega = np.logspace(-1, 2, 1001)
124119

125-
# Laplace variable
126-
s = control.tf('s')
127-
128120
# Loop transfer gain
129121
L = control.tf(25, [1, 10, 10, 10])
130122

131-
print(f"------------- Python control built-in (S) -------------")
123+
print("------------- Python control built-in (S) -------------")
132124
GM_, PM_, SM_ = control.stability_margins(L)[:3] # python-control default (S-based...?)
133125
print(f"SM_ = {SM_}")
134126
print(f"GM_ = {GM_} dB")
135127
print(f"PM_ = {PM_} deg\n")
136128

137-
print(f"------------- Sensitivity function (S) -------------")
129+
print("------------- Sensitivity function (S) -------------")
138130
DM, GM, PM = control.disk_margins(L, omega, skew = 1.0, returnall = True) # S-based (S)
139131
print(f"min(DM) = {min(DM)} (omega = {omega[np.argmin(DM)]})")
140132
print(f"GM = {GM[np.argmin(DM)]} dB")
@@ -173,7 +165,7 @@ def test_siso1():
173165
plt.ylim([0, 90])
174166
plt.xlabel('Frequency (rad/s)')
175167

176-
print(f"------------- Complementary sensitivity function (T) -------------")
168+
print("------------- Complementary sensitivity function (T) -------------")
177169
DM, GM, PM = control.disk_margins(L, omega, skew = -1.0, returnall = True) # T-based (T)
178170
print(f"min(DM) = {min(DM)} (omega = {omega[np.argmin(DM)]})")
179171
print(f"GM = {GM[np.argmin(DM)]} dB")
@@ -212,7 +204,7 @@ def test_siso1():
212204
plt.ylim([0, 90])
213205
plt.xlabel('Frequency (rad/s)')
214206

215-
print(f"------------- Balanced sensitivity function (S - T) -------------")
207+
print("------------- Balanced sensitivity function (S - T) -------------")
216208
DM, GM, PM = control.disk_margins(L, omega, skew = 0.0, returnall = True) # balanced (S - T)
217209
print(f"min(DM) = {min(DM)} (omega = {omega[np.argmin(DM)]})")
218210
print(f"GM = {GM[np.argmin(DM)]} dB")
@@ -276,13 +268,13 @@ def test_siso2():
276268
# Loop transfer gain
277269
L = (6.25*(s + 3)*(s + 5))/(s*(s + 1)**2*(s**2 + 0.18*s + 100))
278270

279-
print(f"------------- Python control built-in (S) -------------")
271+
print("------------- Python control built-in (S) -------------")
280272
GM_, PM_, SM_ = control.stability_margins(L)[:3] # python-control default (S-based...?)
281273
print(f"SM_ = {SM_}")
282274
print(f"GM_ = {GM_} dB")
283275
print(f"PM_ = {PM_} deg\n")
284276

285-
print(f"------------- Sensitivity function (S) -------------")
277+
print("------------- Sensitivity function (S) -------------")
286278
DM, GM, PM = control.disk_margins(L, omega, skew = 1.0, returnall = True) # S-based (S)
287279
print(f"min(DM) = {min(DM)} (omega = {omega[np.argmin(DM)]})")
288280
print(f"GM = {GM[np.argmin(DM)]} dB")
@@ -321,7 +313,7 @@ def test_siso2():
321313
plt.ylim([0, 90])
322314
plt.xlabel('Frequency (rad/s)')
323315

324-
print(f"------------- Complementary sensitivity function (T) -------------")
316+
print("------------- Complementary sensitivity function (T) -------------")
325317
DM, GM, PM = control.disk_margins(L, omega, skew = -1.0, returnall = True) # T-based (T)
326318
print(f"min(DM) = {min(DM)} (omega = {omega[np.argmin(DM)]})")
327319
print(f"GM = {GM[np.argmin(DM)]} dB")
@@ -360,7 +352,7 @@ def test_siso2():
360352
plt.ylim([0, 90])
361353
plt.xlabel('Frequency (rad/s)')
362354

363-
print(f"------------- Balanced sensitivity function (S - T) -------------")
355+
print("------------- Balanced sensitivity function (S - T) -------------")
364356
DM, GM, PM = control.disk_margins(L, omega, skew = 0.0, returnall = True) # balanced (S - T)
365357
print(f"min(DM) = {min(DM)} (omega = {omega[np.argmin(DM)]})")
366358
print(f"GM = {GM[np.argmin(DM)]} dB")
@@ -419,15 +411,12 @@ def test_mimo():
419411
# Frequencies of interest
420412
omega = np.logspace(-1, 3, 1001)
421413

422-
# Laplace variable
423-
s = control.tf('s')
424-
425414
# Loop transfer gain
426415
P = control.ss([[0, 10],[-10, 0]], np.eye(2), [[1, 10], [-10, 1]], [[0, 0],[0, 0]]) # plant
427416
K = control.ss([],[],[], [[1, -2], [0, 1]]) # controller
428417
L = P*K # loop gain
429418

430-
print(f"------------- Sensitivity function (S) -------------")
419+
print("------------- Sensitivity function (S) -------------")
431420
DM, GM, PM = control.disk_margins(L, omega, skew = 1.0, returnall = True) # S-based (S)
432421
print(f"min(DM) = {min(DM)} (omega = {omega[np.argmin(DM)]})")
433422
print(f"GM = {GM[np.argmin(DM)]} dB")
@@ -466,7 +455,7 @@ def test_mimo():
466455
plt.ylim([0, 90])
467456
plt.xlabel('Frequency (rad/s)')
468457

469-
print(f"------------- Complementary sensitivity function (T) -------------")
458+
print("------------- Complementary sensitivity function (T) -------------")
470459
DM, GM, PM = control.disk_margins(L, omega, skew = -1.0, returnall = True) # T-based (T)
471460
print(f"min(DM) = {min(DM)} (omega = {omega[np.argmin(DM)]})")
472461
print(f"GM = {GM[np.argmin(DM)]} dB")
@@ -505,7 +494,7 @@ def test_mimo():
505494
plt.ylim([0, 90])
506495
plt.xlabel('Frequency (rad/s)')
507496

508-
print(f"------------- Balanced sensitivity function (S - T) -------------")
497+
print("------------- Balanced sensitivity function (S - T) -------------")
509498
DM, GM, PM = control.disk_margins(L, omega, skew = 0.0, returnall = True) # balanced (S - T)
510499
print(f"min(DM) = {min(DM)} (omega = {omega[np.argmin(DM)]})")
511500
print(f"GM = {GM[np.argmin(DM)]} dB")

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