[python-control-discuss] SF.net SVN: python-control:[47] branches/control-0.4a/src

[<kk...@us...>]

Revision: 47
          http://python-control.svn.sourceforge.net/python-control/?rev=47&view=rev
Author:   kkchen
Date:     2011-02-08 22:13:36 +0000 (Tue, 08 Feb 2011)

Log Message:
-----------
Added initial unittests for modred and balred to TestModelsimp.py and debugged hsvd.

Lauren Padilla <lpa...@pr...>

Modified Paths:
--------------
    branches/control-0.4a/src/TestModelsimp.py
    branches/control-0.4a/src/modelsimp.py

Modified: branches/control-0.4a/src/TestModelsimp.py
===================================================================
--- branches/control-0.4a/src/TestModelsimp.py	2011-02-08 22:13:30 UTC (rev 46)
+++ branches/control-0.4a/src/TestModelsimp.py	2011-02-08 22:13:36 UTC (rev 47)
@@ -24,5 +24,93 @@
         Htrue = np.matrix("1.; 0.; 0.")
         np.testing.assert_array_almost_equal( H, Htrue )
 
+    def testModredMatchDC(self):
+        #balanced realization computed in matlab for the transfer function:
+        # num = [1 11 45 32], den = [1 15 60 200 60]
+        A = np.matrix('-1.958, -1.194, 1.824, -1.464; \
+        -1.194, -0.8344, 2.563, -1.351; \
+        -1.824, -2.563, -1.124, 2.704; \
+        -1.464, -1.351, -2.704, -11.08')
+        B = np.matrix('-0.9057; -0.4068; -0.3263; -0.3474')
+        C = np.matrix('-0.9057, -0.4068, 0.3263, -0.3474')
+        D = np.matrix('0.')
+        sys = ss(A,B,C,D)
+        rsys = modred(sys,np.matrix('3, 4'),'matchdc')
+        Artrue = np.matrix('-4.431, -4.552; -4.552, -5.361')
+        Brtrue = np.matrix('-1.362; -1.031')
+        Crtrue = np.matrix('-1.362, -1.031')
+        Drtrue = np.matrix('-0.08384')
+        np.testing.assert_array_almost_equal(sys.A, Artrue)
+        np.testing.assert_array_almost_equal(sys.B, Brtrue)
+        np.testing.assert_array_almost_equal(sys.C, Crtrue)
+        np.testing.assert_array_almost_equal(sys.D, Drtrue)
+
+    def testModredTruncate(self):
+        #balanced realization computed in matlab for the transfer function:
+        # num = [1 11 45 32], den = [1 15 60 200 60]
+        A = np.matrix('-1.958, -1.194, 1.824, -1.464; \
+        -1.194, -0.8344, 2.563, -1.351; \
+        -1.824, -2.563, -1.124, 2.704; \
+        -1.464, -1.351, -2.704, -11.08')
+        B = np.matrix('-0.9057; -0.4068; -0.3263; -0.3474')
+        C = np.matrix('-0.9057, -0.4068, 0.3263, -0.3474')
+        D = np.matrix('0.')
+        sys = ss(A,B,C,D)
+        rsys = modred(sys,np.matrix('3, 4'),'truncate')
+        Artrue = np.matrix('-1.958, -1.194; -1.194, -0.8344')
+        Brtrue = np.matrix('-0.9057, -0.4068')
+        Crtrue = np.matrix('-0.9057, -0.4068')
+        Drtrue = np.matrix('0.')
+        np.testing.assert_array_almost_equal(sys.A, Artrue)
+        np.testing.assert_array_almost_equal(sys.B, Brtrue)
+        np.testing.assert_array_almost_equal(sys.C, Crtrue)
+        np.testing.assert_array_almost_equal(sys.D, Drtrue)
+
+    def testBalredMatchDC(self):
+        #controlable canonical realization computed in matlab for the transfer function:
+        # num = [1 11 45 32], den = [1 15 60 200 60]
+        A = np.matrix('-15., -7.5, -6.25, -1.875; \
+        8., 0., 0., 0.; \
+        0., 4., 0., 0.; \
+        0., 0., 1., 0.')
+        B = np.matrix('2.; 0.; 0.; 0.')
+        C = np.matrix('0.5, 0.6875, 0.7031, 0.5')
+        D = np.matrix('0.')
+        sys = ss(A,B,C,D)
+        orders = 1
+        rsys = balred(sys,orders,'elimination','matchdc')
+        Artrue = np.matrix('-0.566')
+        Brtrue = np.matrix('-0.414')
+        Crtrue = np.matrix('-0.5728')
+        Drtrue = np.matrix('0.1145')
+        np.testing.assert_array_almost_equal(sys.A, Artrue)
+        np.testing.assert_array_almost_equal(sys.B, Brtrue)
+        np.testing.assert_array_almost_equal(sys.C, Crtrue)
+        np.testing.assert_array_almost_equal(sys.D, Drtrue)
+
+    def testBalredTruncate(self):
+        #controlable canonical realization computed in matlab for the transfer function:
+        # num = [1 11 45 32], den = [1 15 60 200 60]
+        A = np.matrix('-15., -7.5, -6.25, -1.875; \
+        8., 0., 0., 0.; \
+        0., 4., 0., 0.; \
+        0., 0., 1., 0.')
+        B = np.matrix('2.; 0.; 0.; 0.')
+        C = np.matrix('0.5, 0.6875, 0.7031, 0.5')
+        D = np.matrix('0.')
+        sys = ss(A,B,C,D)
+        orders = 2
+        rsys = balred(sys,orders,'elimination','truncate')
+        Artrue = np.matrix('-1.95, 0.6203; 2.314, -0.8432')
+        Brtrue = np.matrix('0.7221; -0.6306')
+        Crtrue = np.matrix('1.132, -0.2667')
+        Drtrue = np.matrix('0.')
+        np.testing.assert_array_almost_equal(sys.A, Artrue)
+        np.testing.assert_array_almost_equal(sys.B, Brtrue)
+        np.testing.assert_array_almost_equal(sys.C, Crtrue)
+        np.testing.assert_array_almost_equal(sys.D, Drtrue)
+
+
+
 if __name__ == '__main__':
     unittest.main()

Modified: branches/control-0.4a/src/modelsimp.py
===================================================================
--- branches/control-0.4a/src/modelsimp.py	2011-02-08 22:13:30 UTC (rev 46)
+++ branches/control-0.4a/src/modelsimp.py	2011-02-08 22:13:36 UTC (rev 47)
@@ -43,6 +43,7 @@
 import numpy as np
 import ctrlutil
 from control.exception import *
+from statefbk import *
 
 # Hankel Singular Value Decomposition
 #   The following returns the Hankel singular values, which are singular values of the matrix formed by multiplying the controllability and observability grammians
@@ -69,7 +70,7 @@
     Wo = gram(sys,'o')
 
     WoWc = np.dot(Wo, Wc)
-    w, v = LA.eig(WoWc)
+    w, v = np.linalg.eig(WoWc)
 
     hsv = np.sqrt(w)
     hsv = np.matrix(hsv)


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