Added control loops for all the subsystems.
Change-Id: Ie693940734fe0b45f010bb3da0bfb0ec3ba719f5
diff --git a/y2017/control_loops/python/indexer.py b/y2017/control_loops/python/indexer.py
new file mode 100755
index 0000000..a5088cb
--- /dev/null
+++ b/y2017/control_loops/python/indexer.py
@@ -0,0 +1,298 @@
+#!/usr/bin/python
+
+from frc971.control_loops.python import control_loop
+from frc971.control_loops.python import controls
+import numpy
+import sys
+from matplotlib import pylab
+
+import gflags
+import glog
+
+FLAGS = gflags.FLAGS
+
+gflags.DEFINE_bool('plot', False, 'If true, plot the loop response.')
+
+class VelocityIndexer(control_loop.ControlLoop):
+ def __init__(self, name='VelocityIndexer'):
+ super(VelocityIndexer, self).__init__(name)
+ # Stall Torque in N m
+ self.stall_torque = 0.71
+ # Stall Current in Amps
+ self.stall_current = 134
+ # Free Speed in RPM
+ self.free_speed = 18730.0
+ # Free Current in Amps
+ self.free_current = 0.7
+ # Moment of inertia of the indexer halves in kg m^2
+ # This is measured as Iyy in CAD (the moment of inertia around the Y axis).
+ # Inner part of indexer -> Iyy = 59500 lb * mm * mm
+ # Inner spins with 12 / 48 * 18 / 48 * 24 / 36 * 16 / 72
+ # Outer part of indexer -> Iyy = 210000 lb * mm * mm
+ # 1 775 pro -> 12 / 48 * 18 / 48 * 30 / 422
+
+ self.J_inner = 0.0269
+ self.J_outer = 0.0952
+ # Gear ratios for the inner and outer parts.
+ self.G_inner = (12.0 / 48.0) * (18.0 / 48.0) * (24.0 / 36.0) * (16.0 / 72.0)
+ self.G_outer = (12.0 / 48.0) * (18.0 / 48.0) * (30.0 / 422.0)
+
+ # Motor inertia in kg * m^2
+ self.motor_inertia = 0.000006
+
+ # The output coordinate system is in radians for the inner part of the
+ # indexer.
+ # Compute the effective moment of inertia assuming all the mass is in that
+ # coordinate system.
+ self.J = (
+ self.J_inner * self.G_inner * self.G_inner +
+ self.J_outer * self.G_outer * self.G_outer) / (self.G_inner * self.G_inner) + \
+ self.motor_inertia * ((1.0 / self.G_inner) ** 2.0)
+ glog.debug('J is %f', self.J)
+ self.G = self.G_inner
+
+ # Resistance of the motor, divided by 2 to account for the 2 motors
+ self.R = 12.0 / self.stall_current
+ # Motor velocity constant
+ self.Kv = ((self.free_speed / 60.0 * 2.0 * numpy.pi) /
+ (12.0 - self.R * self.free_current))
+ # Torque constant
+ self.Kt = self.stall_torque / self.stall_current
+ # Control loop time step
+ self.dt = 0.005
+
+ # State feedback matrices
+ # [angular velocity]
+ self.A_continuous = numpy.matrix(
+ [[-self.Kt / self.Kv / (self.J * self.G * self.G * self.R)]])
+ self.B_continuous = numpy.matrix(
+ [[self.Kt / (self.J * self.G * self.R)]])
+ self.C = numpy.matrix([[1]])
+ self.D = numpy.matrix([[0]])
+
+ self.A, self.B = self.ContinuousToDiscrete(
+ self.A_continuous, self.B_continuous, self.dt)
+
+ self.PlaceControllerPoles([.82])
+ glog.debug(repr(self.K))
+
+ self.PlaceObserverPoles([0.3])
+
+ self.U_max = numpy.matrix([[12.0]])
+ self.U_min = numpy.matrix([[-12.0]])
+
+ qff_vel = 8.0
+ self.Qff = numpy.matrix([[1.0 / (qff_vel ** 2.0)]])
+
+ self.Kff = controls.TwoStateFeedForwards(self.B, self.Qff)
+ self.InitializeState()
+
+
+class Indexer(VelocityIndexer):
+ def __init__(self, name='Indexer'):
+ super(Indexer, self).__init__(name)
+
+ self.A_continuous_unaugmented = self.A_continuous
+ self.B_continuous_unaugmented = self.B_continuous
+
+ self.A_continuous = numpy.matrix(numpy.zeros((2, 2)))
+ self.A_continuous[1:2, 1:2] = self.A_continuous_unaugmented
+ self.A_continuous[0, 1] = 1
+
+ self.B_continuous = numpy.matrix(numpy.zeros((2, 1)))
+ self.B_continuous[1:2, 0] = self.B_continuous_unaugmented
+
+ # State feedback matrices
+ # [position, angular velocity]
+ self.C = numpy.matrix([[1, 0]])
+ self.D = numpy.matrix([[0]])
+
+ self.A, self.B = self.ContinuousToDiscrete(
+ self.A_continuous, self.B_continuous, self.dt)
+
+ self.rpl = .45
+ self.ipl = 0.07
+ self.PlaceObserverPoles([self.rpl + 1j * self.ipl,
+ self.rpl - 1j * self.ipl])
+
+ self.K_unaugmented = self.K
+ self.K = numpy.matrix(numpy.zeros((1, 2)))
+ self.K[0, 1:2] = self.K_unaugmented
+ self.Kff_unaugmented = self.Kff
+ self.Kff = numpy.matrix(numpy.zeros((1, 2)))
+ self.Kff[0, 1:2] = self.Kff_unaugmented
+
+ self.InitializeState()
+
+
+class IntegralIndexer(Indexer):
+ def __init__(self, name="IntegralIndexer"):
+ super(IntegralIndexer, self).__init__(name=name)
+
+ self.A_continuous_unaugmented = self.A_continuous
+ self.B_continuous_unaugmented = self.B_continuous
+
+ self.A_continuous = numpy.matrix(numpy.zeros((3, 3)))
+ self.A_continuous[0:2, 0:2] = self.A_continuous_unaugmented
+ self.A_continuous[0:2, 2] = self.B_continuous_unaugmented
+
+ self.B_continuous = numpy.matrix(numpy.zeros((3, 1)))
+ self.B_continuous[0:2, 0] = self.B_continuous_unaugmented
+
+ self.C_unaugmented = self.C
+ self.C = numpy.matrix(numpy.zeros((1, 3)))
+ self.C[0:1, 0:2] = self.C_unaugmented
+
+ self.A, self.B = self.ContinuousToDiscrete(
+ self.A_continuous, self.B_continuous, self.dt)
+
+ q_pos = 2.0
+ q_vel = 0.001
+ q_voltage = 10.0
+ self.Q = numpy.matrix([[(q_pos ** 2.0), 0.0, 0.0],
+ [0.0, (q_vel ** 2.0), 0.0],
+ [0.0, 0.0, (q_voltage ** 2.0)]])
+
+ r_pos = 0.001
+ self.R = numpy.matrix([[(r_pos ** 2.0)]])
+
+ self.KalmanGain, self.Q_steady = controls.kalman(
+ A=self.A, B=self.B, C=self.C, Q=self.Q, R=self.R)
+ self.L = self.A * self.KalmanGain
+
+ self.K_unaugmented = self.K
+ self.K = numpy.matrix(numpy.zeros((1, 3)))
+ self.K[0, 0:2] = self.K_unaugmented
+ self.K[0, 2] = 1
+ self.Kff_unaugmented = self.Kff
+ self.Kff = numpy.matrix(numpy.zeros((1, 3)))
+ self.Kff[0, 0:2] = self.Kff_unaugmented
+
+ self.InitializeState()
+
+
+class ScenarioPlotter(object):
+ def __init__(self):
+ # Various lists for graphing things.
+ self.t = []
+ self.x = []
+ self.v = []
+ self.a = []
+ self.x_hat = []
+ self.u = []
+ self.offset = []
+
+ def run_test(self, indexer, goal, iterations=200, controller_indexer=None,
+ observer_indexer=None):
+ """Runs the indexer plant with an initial condition and goal.
+
+ Args:
+ indexer: Indexer object to use.
+ goal: goal state.
+ iterations: Number of timesteps to run the model for.
+ controller_indexer: Indexer object to get K from, or None if we should
+ use indexer.
+ observer_indexer: Indexer object to use for the observer, or None if we
+ should use the actual state.
+ """
+
+ if controller_indexer is None:
+ controller_indexer = indexer
+
+ vbat = 12.0
+
+ if self.t:
+ initial_t = self.t[-1] + indexer.dt
+ else:
+ initial_t = 0
+
+ for i in xrange(iterations):
+ X_hat = indexer.X
+
+ if observer_indexer is not None:
+ X_hat = observer_indexer.X_hat
+ self.x_hat.append(observer_indexer.X_hat[1, 0])
+
+ ff_U = controller_indexer.Kff * (goal - observer_indexer.A * goal)
+
+ U = controller_indexer.K * (goal - X_hat) + ff_U
+ U[0, 0] = numpy.clip(U[0, 0], -vbat, vbat)
+ self.x.append(indexer.X[0, 0])
+
+
+ if self.v:
+ last_v = self.v[-1]
+ else:
+ last_v = 0
+
+ self.v.append(indexer.X[1, 0])
+ self.a.append((self.v[-1] - last_v) / indexer.dt)
+
+ if observer_indexer is not None:
+ observer_indexer.Y = indexer.Y
+ observer_indexer.CorrectObserver(U)
+ self.offset.append(observer_indexer.X_hat[2, 0])
+
+ applied_U = U.copy()
+ if i > 30:
+ applied_U += 2
+ indexer.Update(applied_U)
+
+ if observer_indexer is not None:
+ observer_indexer.PredictObserver(U)
+
+ self.t.append(initial_t + i * indexer.dt)
+ self.u.append(U[0, 0])
+
+ def Plot(self):
+ pylab.subplot(3, 1, 1)
+ pylab.plot(self.t, self.v, label='x')
+ pylab.plot(self.t, self.x_hat, label='x_hat')
+ pylab.legend()
+
+ pylab.subplot(3, 1, 2)
+ pylab.plot(self.t, self.u, label='u')
+ pylab.plot(self.t, self.offset, label='voltage_offset')
+ pylab.legend()
+
+ pylab.subplot(3, 1, 3)
+ pylab.plot(self.t, self.a, label='a')
+ pylab.legend()
+
+ pylab.show()
+
+
+def main(argv):
+ scenario_plotter = ScenarioPlotter()
+
+ indexer = Indexer()
+ indexer_controller = IntegralIndexer()
+ observer_indexer = IntegralIndexer()
+
+ initial_X = numpy.matrix([[0.0], [0.0]])
+ R = numpy.matrix([[0.0], [20.0], [0.0]])
+ scenario_plotter.run_test(indexer, goal=R, controller_indexer=indexer_controller,
+ observer_indexer=observer_indexer, iterations=200)
+
+ if FLAGS.plot:
+ scenario_plotter.Plot()
+
+ if len(argv) != 5:
+ glog.fatal('Expected .h file name and .cc file name')
+ else:
+ namespaces = ['y2017', 'control_loops', 'superstructure', 'indexer']
+ indexer = Indexer('Indexer')
+ loop_writer = control_loop.ControlLoopWriter('Indexer', [indexer],
+ namespaces=namespaces)
+ loop_writer.Write(argv[1], argv[2])
+
+ integral_indexer = IntegralIndexer('IntegralIndexer')
+ integral_loop_writer = control_loop.ControlLoopWriter(
+ 'IntegralIndexer', [integral_indexer], namespaces=namespaces)
+ integral_loop_writer.Write(argv[3], argv[4])
+
+
+if __name__ == '__main__':
+ argv = FLAGS(sys.argv)
+ glog.init()
+ sys.exit(main(argv))