diff --git a/control/tests/xferfcn_test.py b/control/tests/xferfcn_test.py
index fb8ae7c5b..c88dddcde 100644
--- a/control/tests/xferfcn_test.py
+++ b/control/tests/xferfcn_test.py
@@ -468,6 +468,12 @@ def testMinreal2(self):
np.testing.assert_array_almost_equal(H2b.num[0][0], hr.num[0][0])
np.testing.assert_array_almost_equal(H2b.den[0][0], hr.den[0][0])
+ def testMinreal3(self):
+ """Regression test for minreal of tf([1,1],[1,1])"""
+ g = TransferFunction([1,1],[1,1]).minreal()
+ np.testing.assert_array_almost_equal(1.0, g.num[0][0])
+ np.testing.assert_array_almost_equal(1.0, g.den[0][0])
+
def testMIMO(self):
"""Test conversion of a single input, two-output state-space
system against the same TF"""
diff --git a/control/xferfcn.py b/control/xferfcn.py
index 38e6b4198..7556d9049 100644
--- a/control/xferfcn.py
+++ b/control/xferfcn.py
@@ -678,12 +678,9 @@ def minreal(self, tol=None):
# keep this zero
newzeros.append(z)
- # keep result
- if len(newzeros):
- num[i][j] = gain * real(poly(newzeros))
- else:
- num[i][j] = array([gain])
- den[i][j] = real(poly(poles))
+ # poly([]) returns a scalar, but we always want a 1d array
+ num[i][j] = np.atleast_1d(gain * real(poly(newzeros)))
+ den[i][j] = np.atleast_1d(real(poly(poles)))
# end result
return TransferFunction(num, den)
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