blob: edd5b53ba2900922e6b8d8f2079b6d3b2f3e2b41 [file] [log] [blame]
#!/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 Turret(control_loop.ControlLoop):
def __init__(self, name='Turret'):
super(Turret, self).__init__(name)
# Stall Torque in N m
self.stall_torque = 0.71
# Stall Current in Amps
self.stall_current = 134
self.free_speed_rpm = 18730.0
# Free Speed in rotations/second.
self.free_speed = self.free_speed_rpm / 60.0
# Free Current in Amps
self.free_current = 0.7
# Resistance of the motor
self.resistance = 12.0 / self.stall_current
# Motor velocity constant
self.Kv = ((self.free_speed * 2.0 * numpy.pi) /
(12.0 - self.resistance * self.free_current))
# Torque constant
self.Kt = self.stall_torque / self.stall_current
# Gear ratio
self.G = (12.0 / 60.0) * (11.0 / 94.0)
# Motor inertia in kg * m^2
self.motor_inertia = 0.00001187
# Moment of inertia, measured in CAD.
# Extra mass to compensate for friction is added on.
self.J = 0.06 + self.motor_inertia * ((1.0 / self.G) ** 2.0)
glog.info('Turret J is: %f', self.J)
# Control loop time step
self.dt = 0.005
# State is [position, velocity]
# Input is [Voltage]
C1 = self.Kt / (self.resistance * self.J * self.Kv * self.G * self.G)
C2 = self.Kt / (self.J * self.resistance * self.G)
self.A_continuous = numpy.matrix(
[[0, 1],
[0, -C1]])
# Start with the unmodified input
self.B_continuous = numpy.matrix(
[[0],
[C2]])
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)
# Calculate the LQR controller gain
q_pos = 0.20
q_vel = 5.0
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)
# Calculate the feed forwards gain.
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)
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)
self.L = self.A * self.KalmanGain
# 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 IntegralTurret(Turret):
def __init__(self, name='IntegralTurret'):
super(IntegralTurret, 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 = 3.0
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, turret, end_goal,
controller_turret,
observer_turret=None,
iterations=200):
"""Runs the turret plant with an initial condition and goal.
Args:
turret: turret object to use.
end_goal: end_goal state.
controller_turret: Turret object to get K from, or None if we should
use turret.
observer_turret: Turret 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_turret is None:
controller_turret = turret
vbat = 12.0
if self.t:
initial_t = self.t[-1] + turret.dt
else:
initial_t = 0
goal = numpy.concatenate((turret.X, numpy.matrix(numpy.zeros((1, 1)))), axis=0)
profile = TrapezoidProfile(turret.dt)
profile.set_maximum_acceleration(100.0)
profile.set_maximum_velocity(7.0)
profile.SetGoal(goal[0, 0])
U_last = numpy.matrix(numpy.zeros((1, 1)))
for i in xrange(iterations):
observer_turret.Y = turret.Y
observer_turret.CorrectObserver(U_last)
self.offset.append(observer_turret.X_hat[2, 0])
self.x_hat.append(observer_turret.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_turret.Kff * (next_goal - observer_turret.A * goal)
U_uncapped = controller_turret.K * (goal - observer_turret.X_hat) + ff_U
U_uncapped = controller_turret.K * (end_goal - observer_turret.X_hat)
U = U_uncapped.copy()
U[0, 0] = numpy.clip(U[0, 0], -vbat, vbat)
self.x.append(turret.X[0, 0])
if self.v:
last_v = self.v[-1]
else:
last_v = 0
self.v.append(turret.X[1, 0])
self.a.append((self.v[-1] - last_v) / turret.dt)
offset = 0.0
if i > 100:
offset = 2.0
turret.Update(U + offset)
observer_turret.PredictObserver(U)
self.t.append(initial_t + i * turret.dt)
self.u.append(U[0, 0])
ff_U -= U_uncapped - U
goal = controller_turret.A * goal + controller_turret.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_turret.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):
argv = FLAGS(argv)
glog.init()
scenario_plotter = ScenarioPlotter()
turret = Turret()
turret_controller = IntegralTurret()
observer_turret = IntegralTurret()
# Test moving the turret with constant separation.
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[numpy.pi/2.0], [0.0], [0.0]])
scenario_plotter.run_test(turret, end_goal=R,
controller_turret=turret_controller,
observer_turret=observer_turret, iterations=200)
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 turret and integral turret.')
else:
namespaces = ['y2017', 'control_loops', 'superstructure', 'turret']
turret = Turret('Turret')
loop_writer = control_loop.ControlLoopWriter('Turret', [turret],
namespaces=namespaces)
loop_writer.AddConstant(control_loop.Constant(
'kFreeSpeed', '%f', turret.free_speed))
loop_writer.AddConstant(control_loop.Constant(
'kOutputRatio', '%f', turret.G))
loop_writer.Write(argv[1], argv[2])
integral_turret = IntegralTurret('IntegralTurret')
integral_loop_writer = control_loop.ControlLoopWriter(
'IntegralTurret', [integral_turret],
namespaces=namespaces)
integral_loop_writer.Write(argv[3], argv[4])
if __name__ == '__main__':
sys.exit(main(sys.argv))