Copy back a lot of the 2014 code.
Change-Id: I552292d8bd7bce4409e02d254bef06a9cc009568
diff --git a/y2014/control_loops/python/drivetrain.py b/y2014/control_loops/python/drivetrain.py
new file mode 100755
index 0000000..ac05a57
--- /dev/null
+++ b/y2014/control_loops/python/drivetrain.py
@@ -0,0 +1,239 @@
+#!/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 = 4.5
+ # Mass of the robot, in kg.
+ self.m = 68
+ # Radius of the robot, in meters (from last year).
+ self.rb = 0.617998644 / 2.0
+ # Radius of the wheels, in meters.
+ self.r = .04445
+ # Resistance of the motor, divided by the number of motors.
+ self.R = 12.0 / self.stall_current / 4
+ # 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_low = 18.0 / 60.0 * 18.0 / 50.0
+ self.G_high = 28.0 / 50.0 * 18.0 / 50.0
+ 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])
+ 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))