python-control
diff --git a/‎examples/check-controllability-and-observability.py
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diff --git a/‎examples/slicot-test.py
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diff --git a/‎examples/slycot-import-test.py
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diff --git a/‎examples/test-statefbk.py
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+""" check-controllability-and-observability.py
+
+Example to check the controllability and the observability of a state space system.
+RMM, 6 Sep 2010
+"""
+
+from __future__ import print_function
+
+from scipy import *  # Load the scipy functions
+from control.matlab import *  # Load the controls systems library
+
+# Parameters defining the system
+
+m = 250.0  # system mass
+k = 40.0  # spring constant
+b = 60.0  # damping constant
+
+# System matrices
+A = matrix([[1, -1, 1.],
+            [1, -k / m, -b / m],
+            [1, 1, 1]])
+
+B = matrix([[0],
+            [1 / m],
+            [1]])
+
+C = matrix([[1., 0, 1.]])
+
+sys = ss(A, B, C, 0)
+
+# Check controllability
+Wc = ctrb(A, B)
+print("Wc = ", Wc)
+
+# Check Observability
+Wo = obsv(A, C)
+print("Wo = ", Wo)
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+""" slycot-import-test.py
+
+Simple example script to test Slycot import
+RMM, 28 May 09
+"""
+
+import numpy as np
+from scipy import *
+from control.matlab import *
+from control.exception import slycot_check
+
+# Parameters defining the system
+m = 250.0  # system mass
+k = 40.0  # spring constant
+b = 60.0  # damping constant
+
+# System matrices
+A = np.matrix([[1, -1, 1.], [1, -k / m, -b / m], [1, 1, 1]])
+B = np.matrix([[0], [1 / m], [1]])
+C = np.matrix([[1., 0, 1.]])
+sys = ss(A, B, C, 0)
+
+# Python control may be used without slycot, for example for a pole placement.
+# Eigenvalue placement
+w = [-3, -2, -1]
+K = place(A, B, w)
+print("[python-control (from scipy)] K = ", K)
+print("[python-control (from scipy)] eigs = ", np.linalg.eig(A - B * K)[0])
+
+# Before using one of its routine, check that slycot is installed.
+w = np.array([-3, -2, -1])
+if slycot_check():
+    # Import routine sb01bd used for pole placement.
+    from slycot import sb01bd
+
+    n = 3  # Number of states
+    m = 1  # Number of inputs
+    npp = 3 # Number of placed eigen values
+    alpha = 1 # Maximum threshold for eigen values
+    dico = 'D'  # Discrete system
+    _, _, _, _, _, K, _ = sb01bd(n, m, npp, alpha, A, B, w, dico, tol=0.0, ldwork=None)
+    print("[slycot] K = ", K)
+    print("[slycot] eigs = ", np.linalg.eig(A + np.dot(B, K))[0])
+else:
+    print("Slycot is not installed.")