Пример #1
0
    def test_linear_affine_system(self):
        # Just make sure linear system is spelled correctly.
        A = np.identity(2)
        B = np.array([[0], [1]])
        f0 = np.array([[0], [0]])
        C = np.array([[0, 1]])
        D = [0]
        y0 = [0]
        system = LinearSystem(A, B, C, D)
        context = system.CreateDefaultContext()
        self.assertEqual(system.get_input_port(0).size(), 1)
        self.assertEqual(context.get_mutable_continuous_state_vector().size(),
                         2)
        self.assertEqual(system.get_output_port(0).size(), 1)
        self.assertTrue((system.A() == A).all())
        self.assertTrue((system.B() == B).all())
        self.assertTrue((system.f0() == f0).all())
        self.assertTrue((system.C() == C).all())
        self.assertEqual(system.D(), D)
        self.assertEqual(system.y0(), y0)
        self.assertEqual(system.time_period(), 0.)

        Co = ControllabilityMatrix(system)
        self.assertEqual(Co.shape, (2, 2))
        self.assertFalse(IsControllable(system))
        self.assertFalse(IsControllable(system, 1e-6))
        Ob = ObservabilityMatrix(system)
        self.assertEqual(Ob.shape, (2, 2))
        self.assertFalse(IsObservable(system))

        system = AffineSystem(A, B, f0, C, D, y0, .1)
        self.assertEqual(system.get_input_port(0), system.get_input_port())
        self.assertEqual(system.get_output_port(0), system.get_output_port())
        context = system.CreateDefaultContext()
        self.assertEqual(system.get_input_port(0).size(), 1)
        self.assertEqual(context.get_discrete_state_vector().size(), 2)
        self.assertEqual(system.get_output_port(0).size(), 1)
        self.assertTrue((system.A() == A).all())
        self.assertTrue((system.B() == B).all())
        self.assertTrue((system.f0() == f0).all())
        self.assertTrue((system.C() == C).all())
        self.assertEqual(system.D(), D)
        self.assertEqual(system.y0(), y0)
        self.assertEqual(system.time_period(), .1)

        system.get_input_port(0).FixValue(context, 0)
        linearized = Linearize(system, context)
        self.assertTrue((linearized.A() == A).all())
        taylor = FirstOrderTaylorApproximation(system, context)
        self.assertTrue((taylor.y0() == y0).all())

        system = MatrixGain(D=A)
        self.assertTrue((system.D() == A).all())
Пример #2
0
    def test_linear_affine_system(self):
        # Just make sure linear system is spelled correctly.
        A = np.identity(2)
        B = np.array([[0], [1]])
        f0 = np.array([[0], [0]])
        C = np.array([[0, 1]])
        D = [0]
        y0 = [0]
        system = LinearSystem(A, B, C, D)
        context = system.CreateDefaultContext()
        self.assertEqual(system.get_input_port(0).size(), 1)
        self.assertEqual(context
                         .get_mutable_continuous_state_vector().size(), 2)
        self.assertEqual(system.get_output_port(0).size(), 1)
        self.assertTrue((system.A() == A).all())
        self.assertTrue((system.B() == B).all())
        self.assertTrue((system.f0() == f0).all())
        self.assertTrue((system.C() == C).all())
        self.assertEqual(system.D(), D)
        self.assertEqual(system.y0(), y0)
        self.assertEqual(system.time_period(), 0.)

        Co = ControllabilityMatrix(system)
        self.assertEqual(Co.shape, (2, 2))
        self.assertFalse(IsControllable(system))
        self.assertFalse(IsControllable(system, 1e-6))
        Ob = ObservabilityMatrix(system)
        self.assertEqual(Ob.shape, (2, 2))
        self.assertFalse(IsObservable(system))

        system = AffineSystem(A, B, f0, C, D, y0, .1)
        context = system.CreateDefaultContext()
        self.assertEqual(system.get_input_port(0).size(), 1)
        self.assertEqual(context.get_discrete_state_vector().size(), 2)
        self.assertEqual(system.get_output_port(0).size(), 1)
        self.assertTrue((system.A() == A).all())
        self.assertTrue((system.B() == B).all())
        self.assertTrue((system.f0() == f0).all())
        self.assertTrue((system.C() == C).all())
        self.assertEqual(system.D(), D)
        self.assertEqual(system.y0(), y0)
        self.assertEqual(system.time_period(), .1)

        context.FixInputPort(0, BasicVector([0]))
        linearized = Linearize(system, context)
        self.assertTrue((linearized.A() == A).all())
        taylor = FirstOrderTaylorApproximation(system, context)
        self.assertTrue((taylor.y0() == y0).all())

        system = MatrixGain(D=A)
        self.assertTrue((system.D() == A).all())
Пример #3
0
    def test_linear_affine_system(self):
        # Just make sure linear system is spelled correctly.
        A = np.identity(2)
        B = np.array([[0], [1]])
        f0 = np.array([[0], [0]])
        C = np.array([[0, 1]])
        D = [0]
        y0 = [0]
        system = LinearSystem(A, B, C, D)
        context = system.CreateDefaultContext()
        self.assertEqual(system.get_input_port(0).size(), 1)
        self.assertEqual(context.get_mutable_continuous_state_vector().size(),
                         2)
        self.assertEqual(system.get_output_port(0).size(), 1)
        self.assertTrue((system.A() == A).all())
        self.assertTrue((system.B() == B).all())
        self.assertTrue((system.f0() == f0).all())
        self.assertTrue((system.C() == C).all())
        self.assertEqual(system.D(), D)
        self.assertEqual(system.y0(), y0)
        self.assertEqual(system.time_period(), 0.)

        x0 = np.array([1, 2])
        system.configure_default_state(x0=x0)
        system.SetDefaultContext(context)
        np.testing.assert_equal(
            context.get_continuous_state_vector().CopyToVector(), x0)
        generator = RandomGenerator()
        system.SetRandomContext(context, generator)
        np.testing.assert_equal(
            context.get_continuous_state_vector().CopyToVector(), x0)
        system.configure_random_state(covariance=np.eye(2))
        system.SetRandomContext(context, generator)
        self.assertNotEqual(
            context.get_continuous_state_vector().CopyToVector()[1], x0[1])

        Co = ControllabilityMatrix(system)
        self.assertEqual(Co.shape, (2, 2))
        self.assertFalse(IsControllable(system))
        self.assertFalse(IsControllable(system, 1e-6))
        Ob = ObservabilityMatrix(system)
        self.assertEqual(Ob.shape, (2, 2))
        self.assertFalse(IsObservable(system))

        system = AffineSystem(A, B, f0, C, D, y0, .1)
        self.assertEqual(system.get_input_port(0), system.get_input_port())
        self.assertEqual(system.get_output_port(0), system.get_output_port())
        context = system.CreateDefaultContext()
        self.assertEqual(system.get_input_port(0).size(), 1)
        self.assertEqual(context.get_discrete_state_vector().size(), 2)
        self.assertEqual(system.get_output_port(0).size(), 1)
        self.assertTrue((system.A() == A).all())
        self.assertTrue((system.B() == B).all())
        self.assertTrue((system.f0() == f0).all())
        self.assertTrue((system.C() == C).all())
        self.assertEqual(system.D(), D)
        self.assertEqual(system.y0(), y0)
        self.assertEqual(system.time_period(), .1)

        system.get_input_port(0).FixValue(context, 0)
        linearized = Linearize(system, context)
        self.assertTrue((linearized.A() == A).all())
        taylor = FirstOrderTaylorApproximation(system, context)
        self.assertTrue((taylor.y0() == y0).all())

        system = MatrixGain(D=A)
        self.assertTrue((system.D() == A).all())

        system = TrajectoryAffineSystem(PiecewisePolynomial(A),
                                        PiecewisePolynomial(B),
                                        PiecewisePolynomial(f0),
                                        PiecewisePolynomial(C),
                                        PiecewisePolynomial(D),
                                        PiecewisePolynomial(y0), .1)
        self.assertEqual(system.get_input_port(0), system.get_input_port())
        self.assertEqual(system.get_output_port(0), system.get_output_port())
        context = system.CreateDefaultContext()
        self.assertEqual(system.get_input_port(0).size(), 1)
        self.assertEqual(context.get_discrete_state_vector().size(), 2)
        self.assertEqual(system.get_output_port(0).size(), 1)
        for t in np.linspace(0., 1., 5):
            self.assertTrue((system.A(t) == A).all())
            self.assertTrue((system.B(t) == B).all())
            self.assertTrue((system.f0(t) == f0).all())
            self.assertTrue((system.C(t) == C).all())
            self.assertEqual(system.D(t), D)
            self.assertEqual(system.y0(t), y0)
        self.assertEqual(system.time_period(), .1)
        x0 = np.array([1, 2])
        system.configure_default_state(x0=x0)
        system.SetDefaultContext(context)
        np.testing.assert_equal(
            context.get_discrete_state_vector().CopyToVector(), x0)
        generator = RandomGenerator()
        system.SetRandomContext(context, generator)
        np.testing.assert_equal(
            context.get_discrete_state_vector().CopyToVector(), x0)
        system.configure_random_state(covariance=np.eye(2))
        system.SetRandomContext(context, generator)
        self.assertNotEqual(
            context.get_discrete_state_vector().CopyToVector()[1], x0[1])

        system = TrajectoryLinearSystem(A=PiecewisePolynomial(A),
                                        B=PiecewisePolynomial(B),
                                        C=PiecewisePolynomial(C),
                                        D=PiecewisePolynomial(D),
                                        time_period=0.1)
        self.assertEqual(system.time_period(), .1)
        system.configure_default_state(x0=np.array([1, 2]))
        system.configure_random_state(covariance=np.eye(2))