Updated the drivetrain control loop for this year.

Still need a couple unit tests, but the current test passes.
diff --git a/frc971/control_loops/python/drivetrain.py b/frc971/control_loops/python/drivetrain.py
new file mode 100755
index 0000000..e5a8217
--- /dev/null
+++ b/frc971/control_loops/python/drivetrain.py
@@ -0,0 +1,161 @@
+#!/usr/bin/python
+
+import control_loop
+import numpy
+import sys
+from matplotlib import pylab
+
+class Drivetrain(control_loop.ControlLoop):
+  def __init__(self):
+    super(Drivetrain, self).__init__("Drivetrain")
+    # Stall Torque in N m
+    self.stall_torque = 2.42
+    # Stall Current in Amps
+    self.stall_current = 133
+    # 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 = 7.0
+    # 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 / 6
+    # 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 = 16.0 / 60.0 * 19.0 / 50.0
+    self.G_high = 28.0 / 48.0 * 19.0 / 50.0
+    self.G = self.G_low
+    # Control loop time step
+    self.dt = 0.01
+
+    # 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.tc = -self.Kt / self.Kv / (self.G * self.G * self.R * self.r * self.r)
+    self.mp = self.Kt / (self.G * self.R * self.r)
+
+    # State feedback matrices
+    # X will be of the format
+    # [[position1], [velocity1], [position2], velocity2]]
+    self.A_continuous = numpy.matrix(
+        [[0, 1, 0, 0],
+         [0, self.msp * self.tc, 0, self.msn * self.tc],
+         [0, 0, 0, 1],
+         [0, self.msn * self.tc, 0, self.msp * self.tc]])
+    self.B_continuous = numpy.matrix(
+        [[0, 0],
+         [self.msp * self.mp, self.msn * self.mp],
+         [0, 0],
+         [self.msn * self.mp, self.msp * self.mp]])
+    self.C = numpy.matrix([[1, 0, 0, 0],
+                           [0, 0, 1, 0]])
+    self.D = numpy.matrix([[0, 0],
+                           [0, 0]])
+
+    self.ContinuousToDiscrete(self.A_continuous, self.B_continuous,
+                              self.dt, self.C)
+
+    # Poles from last year.
+    self.hp = 0.8
+    self.lp = 0.85
+    self.PlaceControllerPoles([self.hp, self.hp, self.lp, self.lp])
+
+    print self.K
+
+    self.hlp = 0.07
+    self.llp = 0.09
+    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]])
+
+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.
+  if len(argv) != 3:
+    print "Expected .h file name and .cc file name"
+  else:
+    if argv[1][-3:] == '.cc':
+      print '.cc file is second'
+    else:
+      drivetrain.DumpHeaderFile(argv[1])
+      drivetrain.DumpCppFile(argv[2], argv[1])
+
+if __name__ == '__main__':
+  sys.exit(main(sys.argv))