Added control loops for all the subsystems.
Change-Id: Ie693940734fe0b45f010bb3da0bfb0ec3ba719f5
diff --git a/y2017/control_loops/python/intake.py b/y2017/control_loops/python/intake.py
new file mode 100755
index 0000000..41cfc0d
--- /dev/null
+++ b/y2017/control_loops/python/intake.py
@@ -0,0 +1,321 @@
+#!/usr/bin/python
+
+from aos.common.util.trapezoid_profile import TrapezoidProfile
+from frc971.control_loops.python import control_loop
+from frc971.control_loops.python import controls
+import numpy
+import sys
+import matplotlib
+from matplotlib import pylab
+import gflags
+import glog
+
+FLAGS = gflags.FLAGS
+
+try:
+ gflags.DEFINE_bool('plot', False, 'If true, plot the loop response.')
+except gflags.DuplicateFlagError:
+ pass
+
+class Intake(control_loop.ControlLoop):
+ def __init__(self, name='Intake'):
+ super(Intake, self).__init__(name)
+ # Stall Torque in N m
+ self.stall_torque = 0.71
+ # Stall Current in Amps
+ self.stall_current = 134.0
+ # Free Speed in RPM
+ self.free_speed = 18730.0
+ # Free Current in Amps
+ self.free_current = 0.7
+
+ # Resistance of the motor
+ 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
+
+ # (1 / 35.0) * (20.0 / 40.0) -> 16 tooth sprocket on #25 chain
+ # Gear ratio
+ self.G = (1.0 / 35.0) * (20.0 / 40.0)
+ self.r = 16.0 * 0.25 / (2.0 * numpy.pi) * 0.0254
+
+ # Motor inertia in kg m^2
+ self.motor_inertia = 0.00001187
+
+ # 5.4 kg of moving mass for the intake
+ self.mass = 5.4 + self.motor_inertia / ((self.G * self.r) ** 2.0)
+
+ # Control loop time step
+ self.dt = 0.005
+
+ # State is [position, velocity]
+ # Input is [Voltage]
+
+ C1 = self.Kt / (self.G * self.G * self.r * self.r * self.R * self.mass * self.Kv)
+ C2 = self.Kt / (self.G * self.r * self.R * self.mass)
+
+ self.A_continuous = numpy.matrix(
+ [[0, 1],
+ [0, -C1]])
+
+ # Start with the unmodified input
+ self.B_continuous = numpy.matrix(
+ [[0],
+ [C2]])
+ glog.debug(repr(self.A_continuous))
+ glog.debug(repr(self.B_continuous))
+
+ 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)
+
+ controllability = controls.ctrb(self.A, self.B)
+
+ glog.debug('Free speed is %f',
+ -self.B_continuous[1, 0] / self.A_continuous[1, 1] * 12.0)
+
+ q_pos = 0.015
+ q_vel = 0.3
+ self.Q = numpy.matrix([[(1.0 / (q_pos ** 2.0)), 0.0],
+ [0.0, (1.0 / (q_vel ** 2.0))]])
+
+ self.R = numpy.matrix([[(1.0 / (12.0 ** 2.0))]])
+ self.K = controls.dlqr(self.A, self.B, self.Q, self.R)
+
+ q_pos_ff = 0.005
+ q_vel_ff = 1.0
+ self.Qff = numpy.matrix([[(1.0 / (q_pos_ff ** 2.0)), 0.0],
+ [0.0, (1.0 / (q_vel_ff ** 2.0))]])
+
+ self.Kff = controls.TwoStateFeedForwards(self.B, self.Qff)
+
+ glog.debug('K %s', repr(self.K))
+ glog.debug('Poles are %s',
+ repr(numpy.linalg.eig(self.A - self.B * self.K)[0]))
+
+ self.rpl = 0.30
+ self.ipl = 0.10
+ self.PlaceObserverPoles([self.rpl + 1j * self.ipl,
+ self.rpl - 1j * self.ipl])
+
+ glog.debug('L is %s', repr(self.L))
+
+ q_pos = 0.10
+ q_vel = 1.65
+ self.Q = numpy.matrix([[(q_pos ** 2.0), 0.0],
+ [0.0, (q_vel ** 2.0)]])
+
+ r_volts = 0.025
+ self.R = numpy.matrix([[(r_volts ** 2.0)]])
+
+ self.KalmanGain, self.Q_steady = controls.kalman(
+ A=self.A, B=self.B, C=self.C, Q=self.Q, R=self.R)
+
+ glog.debug('Kal %s', repr(self.KalmanGain))
+ self.L = self.A * self.KalmanGain
+ glog.debug('KalL is %s', repr(self.L))
+
+ # The box formed by U_min and U_max must encompass all possible values,
+ # or else Austin's code gets angry.
+ self.U_max = numpy.matrix([[12.0]])
+ self.U_min = numpy.matrix([[-12.0]])
+
+ self.InitializeState()
+
+class IntegralIntake(Intake):
+ def __init__(self, name='IntegralIntake'):
+ super(IntegralIntake, 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 = 0.12
+ q_vel = 2.00
+ q_voltage = 40.0
+ 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 = 0.05
+ 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 = numpy.concatenate((self.Kff, numpy.matrix(numpy.zeros((1, 1)))), axis=1)
+
+ 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, intake, end_goal,
+ controller_intake,
+ observer_intake=None,
+ iterations=200):
+ """Runs the intake plant with an initial condition and goal.
+
+ Args:
+ intake: intake object to use.
+ end_goal: end_goal state.
+ controller_intake: Intake object to get K from, or None if we should
+ use intake.
+ observer_intake: Intake object to use for the observer, or None if we should
+ use the actual state.
+ iterations: Number of timesteps to run the model for.
+ """
+
+ if controller_intake is None:
+ controller_intake = intake
+
+ vbat = 12.0
+
+ if self.t:
+ initial_t = self.t[-1] + intake.dt
+ else:
+ initial_t = 0
+
+ goal = numpy.concatenate((intake.X, numpy.matrix(numpy.zeros((1, 1)))), axis=0)
+
+ profile = TrapezoidProfile(intake.dt)
+ profile.set_maximum_acceleration(10.0)
+ profile.set_maximum_velocity(0.3)
+ profile.SetGoal(goal[0, 0])
+
+ U_last = numpy.matrix(numpy.zeros((1, 1)))
+ for i in xrange(iterations):
+ observer_intake.Y = intake.Y
+ observer_intake.CorrectObserver(U_last)
+
+ self.offset.append(observer_intake.X_hat[2, 0])
+ self.x_hat.append(observer_intake.X_hat[0, 0])
+
+ next_goal = numpy.concatenate(
+ (profile.Update(end_goal[0, 0], end_goal[1, 0]),
+ numpy.matrix(numpy.zeros((1, 1)))),
+ axis=0)
+
+ ff_U = controller_intake.Kff * (next_goal - observer_intake.A * goal)
+
+ U_uncapped = controller_intake.K * (goal - observer_intake.X_hat) + ff_U
+ U_uncapped = controller_intake.K * (end_goal - observer_intake.X_hat)
+ U = U_uncapped.copy()
+ U[0, 0] = numpy.clip(U[0, 0], -vbat, vbat)
+ self.x.append(intake.X[0, 0])
+
+ if self.v:
+ last_v = self.v[-1]
+ else:
+ last_v = 0
+
+ self.v.append(intake.X[1, 0])
+ self.a.append((self.v[-1] - last_v) / intake.dt)
+
+ offset = 0.0
+ if i > 100:
+ offset = 2.0
+ intake.Update(U + offset)
+
+ observer_intake.PredictObserver(U)
+
+ self.t.append(initial_t + i * intake.dt)
+ self.u.append(U[0, 0])
+
+ ff_U -= U_uncapped - U
+ goal = controller_intake.A * goal + controller_intake.B * ff_U
+
+ if U[0, 0] != U_uncapped[0, 0]:
+ profile.MoveCurrentState(
+ numpy.matrix([[goal[0, 0]], [goal[1, 0]]]))
+
+ glog.debug('Time: %f', self.t[-1])
+ glog.debug('goal_error %s', repr(end_goal - goal))
+ glog.debug('error %s', repr(observer_intake.X_hat - end_goal))
+
+ def Plot(self):
+ pylab.subplot(3, 1, 1)
+ pylab.plot(self.t, self.x, 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()
+
+ intake = Intake()
+ intake_controller = IntegralIntake()
+ observer_intake = IntegralIntake()
+
+ # Test moving the intake with constant separation.
+ initial_X = numpy.matrix([[0.0], [0.0]])
+ R = numpy.matrix([[0.1], [0.0], [0.0]])
+ scenario_plotter.run_test(intake, end_goal=R,
+ controller_intake=intake_controller,
+ observer_intake=observer_intake, iterations=400)
+
+ if FLAGS.plot:
+ scenario_plotter.Plot()
+
+ # Write the generated constants out to a file.
+ if len(argv) != 5:
+ glog.fatal('Expected .h file name and .cc file name for the intake and integral intake.')
+ else:
+ namespaces = ['y2017', 'control_loops', 'superstructure', 'intake']
+ intake = Intake('Intake')
+ loop_writer = control_loop.ControlLoopWriter('Intake', [intake],
+ namespaces=namespaces)
+ loop_writer.Write(argv[1], argv[2])
+
+ integral_intake = IntegralIntake('IntegralIntake')
+ integral_loop_writer = control_loop.ControlLoopWriter('IntegralIntake', [integral_intake],
+ namespaces=namespaces)
+ integral_loop_writer.Write(argv[3], argv[4])
+
+if __name__ == '__main__':
+ argv = FLAGS(sys.argv)
+ glog.init()
+ sys.exit(main(argv))