blob: 9742167ef46693bd59514e248889888748d96ca8 [file] [log] [blame]
#!/usr/bin/python
import control_loop
import controls
import numpy
import sys
from matplotlib import pylab
class CIM(control_loop.ControlLoop):
def __init__(self):
super(CIM, self).__init__("CIM")
# Stall Torque in N m
self.stall_torque = 2.42
# Stall Current in Amps
self.stall_current = 133
# Free Speed in RPM
self.free_speed = 4650.0
# Free Current in Amps
self.free_current = 2.7
# Moment of inertia of the CIM in kg m^2
self.J = 0.0001
# 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
# Control loop time step
self.dt = 0.005
# State feedback matrices
self.A_continuous = numpy.matrix(
[[-self.Kt / self.Kv / (self.J * self.R)]])
self.B_continuous = numpy.matrix(
[[self.Kt / (self.J * 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([0.01])
self.PlaceObserverPoles([0.01])
self.U_max = numpy.matrix([[12.0]])
self.U_min = numpy.matrix([[-12.0]])
self.InitializeState()
class Drivetrain(control_loop.ControlLoop):
def __init__(self, name="Drivetrain", left_low=True, right_low=True):
super(Drivetrain, self).__init__(name)
# Stall Torque in N m
self.stall_torque = 2.42
# Stall Current in Amps
self.stall_current = 133.0
# Free Speed in RPM. Used number from last year.
self.free_speed = 4650.0
# Free Current in Amps
self.free_current = 2.7
# Moment of inertia of the drivetrain in kg m^2
# Just borrowed from last year.
self.J = 10
# Mass of the robot, in kg.
self.m = 68
# Radius of the robot, in meters (from last year).
self.rb = 0.9603 / 2.0
# Radius of the wheels, in meters.
self.r = 0.0508
# Resistance of the motor, divided by the number of motors.
self.R = 12.0 / self.stall_current / 2
# 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 ratios
self.G_const = 18.0 / 44.0 * 18.0 / 60.0
self.G_low = self.G_const
self.G_high = self.G_const
if left_low:
self.Gl = self.G_low
else:
self.Gl = self.G_high
if right_low:
self.Gr = self.G_low
else:
self.Gr = self.G_high
# Control loop time step
self.dt = 0.005
# These describe the way that a given side of a robot will be influenced
# by the other side. Units of 1 / kg.
self.msp = 1.0 / self.m + self.rb * self.rb / self.J
self.msn = 1.0 / self.m - self.rb * self.rb / self.J
# The calculations which we will need for A and B.
self.tcl = -self.Kt / self.Kv / (self.Gl * self.Gl * self.R * self.r * self.r)
self.tcr = -self.Kt / self.Kv / (self.Gr * self.Gr * self.R * self.r * self.r)
self.mpl = self.Kt / (self.Gl * self.R * self.r)
self.mpr = self.Kt / (self.Gr * self.R * self.r)
# State feedback matrices
# X will be of the format
# [[positionl], [velocityl], [positionr], velocityr]]
self.A_continuous = numpy.matrix(
[[0, 1, 0, 0],
[0, self.msp * self.tcl, 0, self.msn * self.tcr],
[0, 0, 0, 1],
[0, self.msn * self.tcl, 0, self.msp * self.tcr]])
self.B_continuous = numpy.matrix(
[[0, 0],
[self.msp * self.mpl, self.msn * self.mpr],
[0, 0],
[self.msn * self.mpl, self.msp * self.mpr]])
self.C = numpy.matrix([[1, 0, 0, 0],
[0, 0, 1, 0]])
self.D = numpy.matrix([[0, 0],
[0, 0]])
#print "THE NUMBER I WANT" + str(numpy.linalg.inv(self.A_continuous) * -self.B_continuous * numpy.matrix([[12.0], [12.0]]))
self.A, self.B = self.ContinuousToDiscrete(
self.A_continuous, self.B_continuous, self.dt)
# Poles from last year.
self.hp = 0.65
self.lp = 0.83
self.PlaceControllerPoles([self.hp, self.lp, self.hp, self.lp])
print self.K
q_pos = 0.07
q_vel = 1.0
self.Q = numpy.matrix([[(1.0 / (q_pos ** 2.0)), 0.0, 0.0, 0.0],
[0.0, (1.0 / (q_vel ** 2.0)), 0.0, 0.0],
[0.0, 0.0, (1.0 / (q_pos ** 2.0)), 0.0],
[0.0, 0.0, 0.0, (1.0 / (q_vel ** 2.0))]])
self.R = numpy.matrix([[(1.0 / (12.0 ** 2.0)), 0.0],
[0.0, (1.0 / (12.0 ** 2.0))]])
self.K = controls.dlqr(self.A, self.B, self.Q, self.R)
print self.A
print self.B
print self.K
print numpy.linalg.eig(self.A - self.B * self.K)[0]
self.hlp = 0.3
self.llp = 0.4
self.PlaceObserverPoles([self.hlp, self.hlp, self.llp, self.llp])
self.U_max = numpy.matrix([[12.0], [12.0]])
self.U_min = numpy.matrix([[-12.0], [-12.0]])
self.InitializeState()
def main(argv):
# Simulate the response of the system to a step input.
drivetrain = Drivetrain()
simulated_left = []
simulated_right = []
for _ in xrange(100):
drivetrain.Update(numpy.matrix([[12.0], [12.0]]))
simulated_left.append(drivetrain.X[0, 0])
simulated_right.append(drivetrain.X[2, 0])
#pylab.plot(range(100), simulated_left)
#pylab.plot(range(100), simulated_right)
#pylab.show()
# Simulate forwards motion.
drivetrain = Drivetrain()
close_loop_left = []
close_loop_right = []
R = numpy.matrix([[1.0], [0.0], [1.0], [0.0]])
for _ in xrange(100):
U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
drivetrain.U_min, drivetrain.U_max)
drivetrain.UpdateObserver(U)
drivetrain.Update(U)
close_loop_left.append(drivetrain.X[0, 0])
close_loop_right.append(drivetrain.X[2, 0])
#pylab.plot(range(100), close_loop_left)
#pylab.plot(range(100), close_loop_right)
#pylab.show()
# Try turning in place
drivetrain = Drivetrain()
close_loop_left = []
close_loop_right = []
R = numpy.matrix([[-1.0], [0.0], [1.0], [0.0]])
for _ in xrange(100):
U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
drivetrain.U_min, drivetrain.U_max)
drivetrain.UpdateObserver(U)
drivetrain.Update(U)
close_loop_left.append(drivetrain.X[0, 0])
close_loop_right.append(drivetrain.X[2, 0])
#pylab.plot(range(100), close_loop_left)
#pylab.plot(range(100), close_loop_right)
#pylab.show()
# Try turning just one side.
drivetrain = Drivetrain()
close_loop_left = []
close_loop_right = []
R = numpy.matrix([[0.0], [0.0], [1.0], [0.0]])
for _ in xrange(100):
U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
drivetrain.U_min, drivetrain.U_max)
drivetrain.UpdateObserver(U)
drivetrain.Update(U)
close_loop_left.append(drivetrain.X[0, 0])
close_loop_right.append(drivetrain.X[2, 0])
#pylab.plot(range(100), close_loop_left)
#pylab.plot(range(100), close_loop_right)
#pylab.show()
# Write the generated constants out to a file.
print "Output one"
drivetrain_low_low = Drivetrain(name="DrivetrainLowLow", left_low=True, right_low=True)
drivetrain_low_high = Drivetrain(name="DrivetrainLowHigh", left_low=True, right_low=False)
drivetrain_high_low = Drivetrain(name="DrivetrainHighLow", left_low=False, right_low=True)
drivetrain_high_high = Drivetrain(name="DrivetrainHighHigh", left_low=False, right_low=False)
if len(argv) != 5:
print "Expected .h file name and .cc file name"
else:
dog_loop_writer = control_loop.ControlLoopWriter(
"Drivetrain", [drivetrain_low_low, drivetrain_low_high,
drivetrain_high_low, drivetrain_high_high],
namespaces=['y2015_bot3', 'control_loops'])
if argv[1][-3:] == '.cc':
dog_loop_writer.Write(argv[2], argv[1])
else:
dog_loop_writer.Write(argv[1], argv[2])
if __name__ == '__main__':
sys.exit(main(sys.argv))