def testAcker(self, fixedseed):
for states in range(1, self.maxStates):
for i in range(self.maxTries):
# start with a random SS system and transform to TF then
# back to SS, check that the matrices are the same.
sys = rss(states, 1, 1)
if (self.debug):
print(sys)
# Make sure the system is not degenerate
Cmat = ctrb(sys.A, sys.B)
if np.linalg.matrix_rank(Cmat) != states:
if (self.debug):
print(" skipping (not reachable or ill conditioned)")
continue
# Place the poles at random locations
des = rss(states, 1, 1)
poles = pole(des)
# Now place the poles using acker
K = acker(sys.A, sys.B, poles)
new = ss(sys.A - sys.B * K, sys.B, sys.C, sys.D)
placed = pole(new)
# Debugging code
# diff = np.sort(poles) - np.sort(placed)
# if not all(diff < 0.001):
# print("Found a problem:")
# print(sys)
# print("desired = ", poles)
np.testing.assert_array_almost_equal(np.sort(poles),
np.sort(placed),
decimal=4)
def testAcker(self):
for states in range(1, self.maxStates):
for i in range(self.maxTries):
# start with a random SS system and transform to TF then
# back to SS, check that the matrices are the same.
sys = rss(states, 1, 1)
if (self.debug):
print(sys)
# Make sure the system is not degenerate
Cmat = ctrb(sys.A, sys.B)
if np.linalg.matrix_rank(Cmat) != states:
if (self.debug):
print(" skipping (not reachable or ill conditioned)")
continue
# Place the poles at random locations
des = rss(states, 1, 1);
poles = pole(des)
# Now place the poles using acker
K = acker(sys.A, sys.B, poles)
new = ss(sys.A - sys.B * K, sys.B, sys.C, sys.D)
placed = pole(new)
# Debugging code
# diff = np.sort(poles) - np.sort(placed)
# if not all(diff < 0.001):
# print("Found a problem:")
# print(sys)
# print("desired = ", poles)
np.testing.assert_array_almost_equal(np.sort(poles),
np.sort(placed), decimal=4)
