blob: 7324b18bdce4dba381fa72a5c710932e4eba23d0 [file] [log] [blame]
#!/usr/bin/python
from frc971.control_loops.python import control_loop
import argparse
import numpy
import sys
from matplotlib import pylab
class SprungShooter(control_loop.ControlLoop):
def __init__(self, name="RawSprungShooter", verbose=False):
super(SprungShooter, self).__init__(name)
# Stall Torque in N m
self.stall_torque = .4982
# Stall Current in Amps
self.stall_current = 85
# Free Speed in RPM
self.free_speed = 19300.0
# Free Current in Amps
self.free_current = 1.2
# Effective mass of the shooter in kg.
# This rough estimate should about include the effect of the masses
# of the gears. If this number is too low, the eigen values of self.A
# will start to become extremely small.
self.J = 200
# Resistance of the motor, divided by the number of motors.
self.R = 12.0 / self.stall_current / 2.0
# 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
# Spring constant for the springs, N/m
self.Ks = 2800.0
# Maximum extension distance (Distance from the 0 force point on the
# spring to the latch position.)
self.max_extension = 0.32385
# Gear ratio multiplied by radius of final sprocket.
self.G = 10.0 / 40.0 * 20.0 / 54.0 * 24.0 / 54.0 * 20.0 / 84.0 * 16.0 * (3.0 / 8.0) / (2.0 * numpy.pi) * 0.0254
# Control loop time step
self.dt = 0.01
# State feedback matrices
self.A_continuous = numpy.matrix(
[[0, 1],
[-self.Ks / self.J,
-self.Kt / self.Kv / (self.J * self.G * self.G * self.R)]])
self.B_continuous = numpy.matrix(
[[0],
[self.Kt / (self.J * self.G * self.R)]])
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.PlaceControllerPoles([0.45, 0.45])
self.rpl = .05
self.ipl = 0.008
self.PlaceObserverPoles([self.rpl,
self.rpl])
self.U_max = numpy.matrix([[12.0]])
self.U_min = numpy.matrix([[-12.0]])
self.InitializeState()
class Shooter(SprungShooter):
def __init__(self, name="RawShooter", verbose=False):
super(Shooter, self).__init__(name)
# State feedback matrices
self.A_continuous = numpy.matrix(
[[0, 1],
[0, -self.Kt / self.Kv / (self.J * self.G * self.G * self.R)]])
self.B_continuous = numpy.matrix(
[[0],
[self.Kt / (self.J * self.G * self.R)]])
self.A, self.B = self.ContinuousToDiscrete(
self.A_continuous, self.B_continuous, self.dt)
self.PlaceControllerPoles([0.45, 0.45])
self.rpl = .05
self.ipl = 0.008
self.PlaceObserverPoles([self.rpl,
self.rpl])
self.U_max = numpy.matrix([[12.0]])
self.U_min = numpy.matrix([[-12.0]])
self.InitializeState()
class SprungShooterDeltaU(SprungShooter):
def __init__(self, name="SprungShooter", verbose=False):
super(SprungShooterDeltaU, self).__init__(name)
A_unaugmented = self.A
B_unaugmented = self.B
self.A = numpy.matrix([[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[0.0, 0.0, 1.0]])
self.A[0:2, 0:2] = A_unaugmented
self.A[0:2, 2] = B_unaugmented
self.B = numpy.matrix([[0.0],
[0.0],
[1.0]])
self.C = numpy.matrix([[1.0, 0.0, 0.0]])
self.D = numpy.matrix([[0.0]])
self.PlaceControllerPoles([0.50, 0.35, 0.80])
if verbose:
print "K"
print self.K
print "Placed controller poles are"
print numpy.linalg.eig(self.A - self.B * self.K)[0]
self.rpl = .05
self.ipl = 0.008
self.PlaceObserverPoles([self.rpl + 1j * self.ipl,
self.rpl - 1j * self.ipl, 0.90])
if verbose:
print "Placed observer poles are"
print numpy.linalg.eig(self.A - self.L * self.C)[0]
self.U_max = numpy.matrix([[12.0]])
self.U_min = numpy.matrix([[-12.0]])
self.InitializeState()
class ShooterDeltaU(Shooter):
def __init__(self, name="Shooter", verbose=False):
super(ShooterDeltaU, self).__init__(name)
A_unaugmented = self.A
B_unaugmented = self.B
self.A = numpy.matrix([[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[0.0, 0.0, 1.0]])
self.A[0:2, 0:2] = A_unaugmented
self.A[0:2, 2] = B_unaugmented
self.B = numpy.matrix([[0.0],
[0.0],
[1.0]])
self.C = numpy.matrix([[1.0, 0.0, 0.0]])
self.D = numpy.matrix([[0.0]])
self.PlaceControllerPoles([0.55, 0.45, 0.80])
if verbose:
print "K"
print self.K
print "Placed controller poles are"
print numpy.linalg.eig(self.A - self.B * self.K)[0]
self.rpl = .05
self.ipl = 0.008
self.PlaceObserverPoles([self.rpl + 1j * self.ipl,
self.rpl - 1j * self.ipl, 0.90])
if verbose:
print "Placed observer poles are"
print numpy.linalg.eig(self.A - self.L * self.C)[0]
self.U_max = numpy.matrix([[12.0]])
self.U_min = numpy.matrix([[-12.0]])
self.InitializeState()
def ClipDeltaU(shooter, old_voltage, delta_u):
old_u = old_voltage
new_u = numpy.clip(old_u + delta_u, shooter.U_min, shooter.U_max)
return new_u - old_u
def main(argv):
parser = argparse.ArgumentParser(description='Calculate shooter.')
parser.add_argument('--plot', action='store_true', default=False, help='If true, plot')
parser.add_argument('shootercc')
parser.add_argument('shooterh')
parser.add_argument('unaugmented_shootercc')
parser.add_argument('unaugmented_shooterh')
args = parser.parse_args(argv[1:])
# Simulate the response of the system to a goal.
sprung_shooter = SprungShooterDeltaU(verbose=args.plot)
raw_sprung_shooter = SprungShooter(verbose=args.plot)
close_loop_x = []
close_loop_u = []
goal_position = -0.3
R = numpy.matrix([[goal_position],
[0.0],
[-sprung_shooter.A[1, 0] / sprung_shooter.A[1, 2] *
goal_position]])
voltage = numpy.matrix([[0.0]])
for _ in xrange(500):
U = sprung_shooter.K * (R - sprung_shooter.X_hat)
U = ClipDeltaU(sprung_shooter, voltage, U)
sprung_shooter.Y = raw_sprung_shooter.Y + 0.01
sprung_shooter.UpdateObserver(U)
voltage += U;
raw_sprung_shooter.Update(voltage)
close_loop_x.append(raw_sprung_shooter.X[0, 0] * 10)
close_loop_u.append(voltage[0, 0])
if args.plot:
pylab.plot(range(500), close_loop_x)
pylab.plot(range(500), close_loop_u)
pylab.show()
shooter = ShooterDeltaU(verbose=args.plot)
raw_shooter = Shooter(verbose=args.plot)
close_loop_x = []
close_loop_u = []
goal_position = -0.3
R = numpy.matrix([[goal_position], [0.0], [-shooter.A[1, 0] / shooter.A[1, 2] * goal_position]])
voltage = numpy.matrix([[0.0]])
for _ in xrange(500):
U = shooter.K * (R - shooter.X_hat)
U = ClipDeltaU(shooter, voltage, U)
shooter.Y = raw_shooter.Y + 0.01
shooter.UpdateObserver(U)
voltage += U;
raw_shooter.Update(voltage)
close_loop_x.append(raw_shooter.X[0, 0] * 10)
close_loop_u.append(voltage[0, 0])
if args.plot:
pylab.plot(range(500), close_loop_x)
pylab.plot(range(500), close_loop_u)
pylab.show()
# Write the generated constants out to a file.
unaug_sprung_shooter = SprungShooter("RawSprungShooter", verbose=args.plot)
unaug_shooter = Shooter("RawShooter", verbose=args.plot)
namespaces = ['y2014', 'control_loops', 'shooter']
unaug_loop_writer = control_loop.ControlLoopWriter("RawShooter",
[unaug_sprung_shooter,
unaug_shooter],
namespaces=namespaces)
unaug_loop_writer.Write(args.unaugmented_shooterh,
args.unaugmented_shootercc)
sprung_shooter = SprungShooterDeltaU(verbose=args.plot)
shooter = ShooterDeltaU(verbose=args.plot)
loop_writer = control_loop.ControlLoopWriter("Shooter",
[sprung_shooter, shooter],
namespaces=namespaces)
loop_writer.AddConstant(control_loop.Constant("kMaxExtension", "%f",
sprung_shooter.max_extension))
loop_writer.AddConstant(control_loop.Constant("kSpringConstant", "%f",
sprung_shooter.Ks))
loop_writer.AddConstant(control_loop.Constant("kDt", "%f",
sprung_shooter.dt))
loop_writer.Write(args.shooterh, args.shootercc)
if __name__ == '__main__':
sys.exit(main(sys.argv))