blob: c9ded12345815624479454cf0806020ef3513de5 [file] [log] [blame]
#!/usr/bin/python
import control_loop
import controls
import numpy
import sys
import matplotlib
from matplotlib import pylab
class Elevator(control_loop.ControlLoop):
def __init__(self, name="Elevator", mass=None):
super(Elevator, self).__init__(name)
# Stall Torque in N m
self.stall_torque = 2.402
# Stall Current in Amps
self.stall_current = 126.145
# Free Speed in RPM
self.free_speed = 5015.562
# Free Current in Amps
self.free_current = 1.170
# Mass of the Elevator
if mass is None:
self.mass = 5.0
else:
self.mass = mass
# Number of motors
self.num_motors = 2.0
# Resistance of the motor
self.resistance = 12.0 / self.stall_current
# Motor velocity constant
self.Kv = ((self.free_speed / 60.0 * 2.0 * numpy.pi) /
(12.0 - self.resistance * self.free_current))
# Torque constant
self.Kt = (self.num_motors * self.stall_torque) / self.stall_current
# Gear ratio
self.G = 8
# Radius of pulley
self.r = 0.0254
# Control loop time step
self.dt = 0.005
# State is [position, velocity]
# Input is [Voltage]
C1 = self.Kt * self.G * self.G / (self.Kv * self.resistance * self.r * self.r * self.mass)
C2 = self.G * self.Kt / (self.resistance * 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]])
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)
controlability = controls.ctrb(self.A, self.B);
q_pos = 0.015
q_vel = 0.5
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)
print 'K', self.K
print 'Poles are', 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])
# print 'L is', self.L
q_pos = 0.05
q_vel = 2.65
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)
# print 'Kal', self.KalmanGain
self.L = self.A * self.KalmanGain
print 'KalL is', 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 IntegralElevator(Elevator):
def __init__(self, name="IntegralElevator", mass=None):
super(IntegralElevator, self).__init__(name=name, mass=mass)
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 = 0.08
q_vel = 4.00
q_voltage = 6.0
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.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 = []
def run_test(self, elevator, goal,
iterations=200, controller_elevator=None,
observer_elevator=None):
"""Runs the Elevator plant with an initial condition and goal.
Args:
Elevator: elevator object to use.
initial_X: starting state.
goal: goal state.
iterations: Number of timesteps to run the model for.
controller_Elevator: elevator object to get K from, or None if we should
use Elevator.
observer_Elevator: elevator object to use for the observer, or None if we should
use the actual state.
"""
if controller_elevator is None:
controller_elevator = elevator
vbat = 10.0
if self.t:
initial_t = self.t[-1] + elevator.dt
else:
initial_t = 0
for i in xrange(iterations):
X_hat = elevator.X
if observer_elevator is not None:
X_hat = observer_elevator.X_hat
self.x_hat.append(observer_elevator.X_hat[0, 0])
gravity_compensation = 9.8 * elevator.mass * elevator.r / elevator.G / elevator.Kt * elevator.resistance
U = controller_elevator.K * (goal - X_hat)
U[0, 0] = numpy.clip(U[0, 0], -vbat , vbat )
self.x.append(elevator.X[0, 0])
if self.v:
last_v = self.v[-1]
else:
last_v = 0
self.v.append(elevator.X[1, 0])
self.a.append((self.v[-1] - last_v) / elevator.dt)
if observer_elevator is not None:
observer_elevator.Y = elevator.Y
observer_elevator.CorrectObserver(U)
elevator.Update(U - gravity_compensation)
if observer_elevator is not None:
observer_elevator.PredictObserver(U)
self.t.append(initial_t + i * elevator.dt)
self.u.append(U[0, 0])
# if numpy.abs((goal - X_hat)[0:2, 0]).sum() < .025:
# print "Time: ", self.t[-1]
# break
print "Time: ", self.t[-1]
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.subplot(3, 1, 3)
pylab.plot(self.t, self.a, label='a')
pylab.legend()
pylab.show()
def main(argv):
loaded_mass = 7+4.0
#loaded_mass = 0
#observer_elevator = None
# Test moving the Elevator
initial_X = numpy.matrix([[0.0], [0.0]])
up_R = numpy.matrix([[0.4572], [0.0], [0.0]])
down_R = numpy.matrix([[0.0], [0.0], [0.0]])
totemass = 3.54
scenario_plotter = ScenarioPlotter()
elevator_controller = IntegralElevator(mass=4*totemass + loaded_mass)
observer_elevator = IntegralElevator(mass=4*totemass + loaded_mass)
for i in xrange(0, 7):
elevator = Elevator(mass=i*totemass + loaded_mass)
print 'Actual poles are', numpy.linalg.eig(elevator.A - elevator.B * elevator_controller.K[0, 0:2])[0]
elevator.X = initial_X
scenario_plotter.run_test(elevator, goal=up_R, controller_elevator=elevator_controller,
observer_elevator=observer_elevator, iterations=200)
scenario_plotter.run_test(elevator, goal=down_R, controller_elevator=elevator_controller,
observer_elevator=observer_elevator, iterations=200)
scenario_plotter.Plot()
# Write the generated constants out to a file.
if len(argv) != 5:
print "Expected .h file name and .cc file name for the Elevator and integral elevator."
else:
design_mass = 4*totemass + loaded_mass
elevator = Elevator("Elevator", mass=design_mass)
loop_writer = control_loop.ControlLoopWriter("Elevator", [elevator],
namespaces=['bot3', 'control_loops'])
if argv[1][-3:] == '.cc':
loop_writer.Write(argv[2], argv[1])
else:
loop_writer.Write(argv[1], argv[2])
integral_elevator = IntegralElevator("IntegralElevator", mass=design_mass)
integral_loop_writer = control_loop.ControlLoopWriter("IntegralElevator", [integral_elevator],
namespaces=['bot3', 'control_loops'])
if argv[3][-3:] == '.cc':
integral_loop_writer.Write(argv[4], argv[3])
else:
integral_loop_writer.Write(argv[3], argv[4])
if __name__ == '__main__':
sys.exit(main(sys.argv))