y2014/control_loops/python/shooter.py

#!/usr/bin/python3

import gflags
import glog
import argparse
import numpy
import sys
from matplotlib import pylab

from frc971.control_loops.python import control_loop

FLAGS = gflags.FLAGS

gflags.DEFINE_bool('plot', False, 'If true, plot the loop response.')


class SprungShooter(control_loop.ControlLoop):

    def __init__(self, name="RawSprungShooter"):
        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 = 0.005

        # 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([0.4501, 0.4499])

        self.PlaceObserverPoles([0.05001, 0.04999])

        self.U_max = numpy.matrix([[12.0]])
        self.U_min = numpy.matrix([[-12.0]])

        self.InitializeState()


class Shooter(SprungShooter):

    def __init__(self, name="RawShooter"):
        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([0.45001, 0.44999])

        self.PlaceObserverPoles([0.05001, 0.04999])

        self.U_max = numpy.matrix([[12.0]])
        self.U_min = numpy.matrix([[-12.0]])

        self.InitializeState()


class SprungShooterDeltaU(SprungShooter):

    def __init__(self, name="SprungShooter"):
        super(SprungShooterDeltaU, self).__init__(name)
        A_unaugmented = self.A
        B_unaugmented = self.B

        A_continuous_unaugmented = self.A_continuous
        B_continuous_unaugmented = self.B_continuous

        self.A_continuous = numpy.matrix(numpy.zeros((3, 3)))
        self.A_continuous[0:2, 0:2] = A_continuous_unaugmented
        self.A_continuous[0:2, 2] = B_continuous_unaugmented

        self.B_continuous = numpy.matrix(numpy.zeros((3, 1)))
        self.B_continuous[2, 0] = 1.0 / self.dt

        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])

        glog.debug('K')
        glog.debug(str(self.K))
        glog.debug('Placed controller poles are')
        glog.debug(str(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])
        glog.debug('Placed observer poles are')
        glog.debug(str(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"):
        super(ShooterDeltaU, self).__init__(name)
        A_unaugmented = self.A
        B_unaugmented = self.B

        A_continuous_unaugmented = self.A_continuous
        B_continuous_unaugmented = self.B_continuous

        self.A_continuous = numpy.matrix(numpy.zeros((3, 3)))
        self.A_continuous[0:2, 0:2] = A_continuous_unaugmented
        self.A_continuous[0:2, 2] = B_continuous_unaugmented

        self.B_continuous = numpy.matrix(numpy.zeros((3, 1)))
        self.B_continuous[2, 0] = 1.0 / self.dt

        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])

        glog.debug('K')
        glog.debug(str(self.K))
        glog.debug('Placed controller poles are')
        glog.debug(str(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])
        glog.debug('Placed observer poles are')
        glog.debug(str(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):
    argv = FLAGS(argv)

    # Simulate the response of the system to a goal.
    sprung_shooter = SprungShooterDeltaU()
    raw_sprung_shooter = SprungShooter()
    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 range(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 FLAGS.plot:
        pylab.plot(range(500), close_loop_x)
        pylab.plot(range(500), close_loop_u)
        pylab.show()

    shooter = ShooterDeltaU()
    raw_shooter = Shooter()
    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 range(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 FLAGS.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")
    unaug_shooter = Shooter("RawShooter")
    namespaces = ['y2014', 'control_loops', 'shooter']
    unaug_loop_writer = control_loop.ControlLoopWriter(
        "RawShooter", [unaug_sprung_shooter, unaug_shooter],
        namespaces=namespaces)
    unaug_loop_writer.Write(argv[4], argv[3])

    sprung_shooter = SprungShooterDeltaU()
    shooter = ShooterDeltaU()
    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(argv[2], argv[1])


if __name__ == '__main__':
    sys.exit(main(sys.argv))