def test_simulation(self):
# Basic constant-torque acrobot simulation.
acrobot = AcrobotPlant()
# Create the simulator.
simulator = Simulator(acrobot)
context = simulator.get_mutable_context()
# Set an input torque.
input = AcrobotInput()
input.set_tau(1.)
acrobot.GetInputPort("elbow_torque").FixValue(context, input)
# Set the initial state.
state = context.get_mutable_continuous_state_vector()
state.set_theta1(1.)
state.set_theta1dot(0.)
state.set_theta2(0.)
state.set_theta2dot(0.)
self.assertTrue(acrobot.DynamicsBiasTerm(context).shape == (2, ))
self.assertTrue(acrobot.MassMatrix(context).shape == (2, 2))
initial_total_energy = acrobot.EvalPotentialEnergy(context) + \
acrobot.EvalKineticEnergy(context)
# Simulate (and make sure the state actually changes).
initial_state = state.CopyToVector()
simulator.AdvanceTo(1.0)
self.assertLessEqual(
acrobot.EvalPotentialEnergy(context) +
acrobot.EvalKineticEnergy(context), initial_total_energy)
def test_simulation(self):
# Basic constant-torque acrobot simulation.
acrobot = AcrobotPlant()
# Create the simulator.
simulator = Simulator(acrobot)
context = simulator.get_mutable_context()
# Set an input torque.
input = AcrobotInput()
input.set_tau(1.)
context.FixInputPort(0, input)
# Set the initial state.
state = context.get_mutable_continuous_state_vector()
state.set_theta1(1.)
state.set_theta1dot(0.)
state.set_theta2(0.)
state.set_theta2dot(0.)
self.assertTrue(acrobot.DynamicsBiasTerm(context).shape == (2,))
self.assertTrue(acrobot.MassMatrix(context).shape == (2, 2))
initial_total_energy = acrobot.CalcPotentialEnergy(context) + \
acrobot.CalcKineticEnergy(context)
# Simulate (and make sure the state actually changes).
initial_state = state.CopyToVector()
simulator.StepTo(1.0)
self.assertLessEqual(acrobot.CalcPotentialEnergy(context) +
acrobot.CalcKineticEnergy(context),
initial_total_energy)
def BalancingLQR():
# Design an LQR controller for stabilizing the Acrobot around the upright.
# Returns a (static) AffineSystem that implements the controller (in
# the original AcrobotState coordinates).
acrobot = AcrobotPlant()
context = acrobot.CreateDefaultContext()
input = AcrobotInput()
input.set_tau(0.)
context.FixInputPort(0, input)
context.get_mutable_continuous_state_vector()\
.SetFromVector(UprightState().CopyToVector())
Q = np.diag((10., 10., 1., 1.))
R = [1]
return LinearQuadraticRegulator(acrobot, context, Q, R)
def BalancingLQR():
# Design an LQR controller for stabilizing the Acrobot around the upright.
# Returns a (static) AffineSystem that implements the controller (in
# the original AcrobotState coordinates).
acrobot = AcrobotPlant()
context = acrobot.CreateDefaultContext()
input = AcrobotInput()
input.set_tau(0.)
context.FixInputPort(0, input)
context.get_mutable_continuous_state_vector()\
.SetFromVector(UprightState().CopyToVector())
Q = np.diag((10., 10., 1., 1.))
R = [1]
return LinearQuadraticRegulator(acrobot, context, Q, R)
def test_input(self):
input = AcrobotInput()
input.set_tau(1.)
self.assertEqual(input.tau(), 1.)
def test_input(self):
input = AcrobotInput()
input.set_tau(1.)
self.assertEqual(input.tau(), 1.)