blob: d7c505b2c859eda65941b2bbe9443d8492a1e890 [file] [log] [blame]
#!/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 VelocityShooter(control_loop.ControlLoop):
def __init__(self, name='VelocityShooter'):
super(VelocityShooter, self).__init__(name)
# Number of motors
self.num_motors = 2.0
# Stall Torque in N m
self.stall_torque = 0.71 * self.num_motors
# Stall Current in Amps
self.stall_current = 134.0 * self.num_motors
# Free Speed in RPM
self.free_speed = 18730.0
# Free Current in Amps
self.free_current = 0.7 * self.num_motors
# Moment of inertia of the shooter wheel in kg m^2
# 1400.6 grams/cm^2
# 1.407 *1e-4 kg m^2
self.J = 0.00080
# 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
# Gear ratio
self.G = 12.0 / 36.0
# 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([.90])
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 Shooter(VelocityShooter):
def __init__(self, name='Shooter'):
super(Shooter, 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 IntegralShooter(Shooter):
def __init__(self, name='IntegralShooter'):
super(IntegralShooter, 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, shooter, goal, iterations=200, controller_shooter=None,
observer_shooter=None):
"""Runs the shooter plant with an initial condition and goal.
Args:
shooter: Shooter object to use.
goal: goal state.
iterations: Number of timesteps to run the model for.
controller_shooter: Shooter object to get K from, or None if we should
use shooter.
observer_shooter: Shooter object to use for the observer, or None if we
should use the actual state.
"""
if controller_shooter is None:
controller_shooter = shooter
vbat = 12.0
if self.t:
initial_t = self.t[-1] + shooter.dt
else:
initial_t = 0
for i in xrange(iterations):
X_hat = shooter.X
if observer_shooter is not None:
X_hat = observer_shooter.X_hat
self.x_hat.append(observer_shooter.X_hat[1, 0])
ff_U = controller_shooter.Kff * (goal - observer_shooter.A * goal)
U = controller_shooter.K * (goal - X_hat) + ff_U
U[0, 0] = numpy.clip(U[0, 0], -vbat, vbat)
self.x.append(shooter.X[0, 0])
if self.v:
last_v = self.v[-1]
else:
last_v = 0
self.v.append(shooter.X[1, 0])
self.a.append((self.v[-1] - last_v) / shooter.dt)
if observer_shooter is not None:
observer_shooter.Y = shooter.Y
observer_shooter.CorrectObserver(U)
self.offset.append(observer_shooter.X_hat[2, 0])
applied_U = U.copy()
if i > 30:
applied_U += 2
shooter.Update(applied_U)
if observer_shooter is not None:
observer_shooter.PredictObserver(U)
self.t.append(initial_t + i * shooter.dt)
self.u.append(U[0, 0])
glog.debug('Time: %f', self.t[-1])
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()
shooter = Shooter()
shooter_controller = IntegralShooter()
observer_shooter = IntegralShooter()
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[0.0], [100.0], [0.0]])
scenario_plotter.run_test(shooter, goal=R, controller_shooter=shooter_controller,
observer_shooter=observer_shooter, 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', 'shooter']
shooter = Shooter('Shooter')
loop_writer = control_loop.ControlLoopWriter('Shooter', [shooter],
namespaces=namespaces)
loop_writer.Write(argv[1], argv[2])
integral_shooter = IntegralShooter('IntegralShooter')
integral_loop_writer = control_loop.ControlLoopWriter(
'IntegralShooter', [integral_shooter], namespaces=namespaces)
integral_loop_writer.Write(argv[3], argv[4])
if __name__ == '__main__':
argv = FLAGS(sys.argv)
glog.init()
sys.exit(main(argv))