Refactor linear_system out of 2017 intake
So we can reuse it!
Change-Id: I0583dbd1fd1a8765468f861a9acba0194aaa8ef6
diff --git a/y2017/control_loops/python/intake.py b/y2017/control_loops/python/intake.py
index 64998c7..015fdfa 100755
--- a/y2017/control_loops/python/intake.py
+++ b/y2017/control_loops/python/intake.py
@@ -1,318 +1,51 @@
#!/usr/bin/python
-from aos.util.trapezoid_profile import TrapezoidProfile
from frc971.control_loops.python import control_loop
-from frc971.control_loops.python import controls
+from frc971.control_loops.python import linear_system
import numpy
import sys
-from matplotlib import pylab
import gflags
import glog
FLAGS = gflags.FLAGS
try:
- gflags.DEFINE_bool('plot', False, 'If true, plot the loop response.')
+ gflags.DEFINE_bool('plot', False, 'If true, plot the loop response.')
except gflags.DuplicateFlagError:
- pass
+ pass
-class Intake(control_loop.ControlLoop):
- def __init__(self, name='Intake'):
- super(Intake, self).__init__(name)
- # Stall Torque in N m
- self.stall_torque = 0.71
- # Stall Current in Amps
- self.stall_current = 134.0
- self.free_speed_rpm = 18730.0
- # Free Speed in rotations/second.
- self.free_speed = self.free_speed_rpm / 60.0
- # Free Current in Amps
- self.free_current = 0.7
-
- # Resistance of the motor
- self.R = 12.0 / self.stall_current
- # Motor velocity constant
- self.Kv = ((self.free_speed * 2.0 * numpy.pi) /
- (12.0 - self.R * self.free_current))
- # Torque constant
- self.Kt = self.stall_torque / self.stall_current
-
+kIntake = linear_system.LinearSystemParams(
+ name='Intake',
+ motor=control_loop.Vex775Pro(),
# (1 / 35.0) * (20.0 / 40.0) -> 16 tooth sprocket on #25 chain
- # Gear ratio
- self.G = (1.0 / 35.0) * (20.0 / 40.0)
- self.r = 16.0 * 0.25 / (2.0 * numpy.pi) * 0.0254
-
- # Motor inertia in kg m^2
- self.motor_inertia = 0.00001187
-
- # 5.4 kg of moving mass for the intake
- self.mass = 5.4 + self.motor_inertia / ((self.G * self.r) ** 2.0)
-
- # Control loop time step
- self.dt = 0.005
-
- # State is [position, velocity]
- # Input is [Voltage]
-
- C1 = self.Kt / (self.G * self.G * self.r * self.r * self.R * self.mass * self.Kv)
- C2 = self.Kt / (self.G * self.r * 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]])
- glog.debug(repr(self.A_continuous))
- glog.debug(repr(self.B_continuous))
-
- 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)
-
- controllability = controls.ctrb(self.A, self.B)
-
- glog.debug('Free speed is %f',
- -self.B_continuous[1, 0] / self.A_continuous[1, 1] * 12.0)
-
- q_pos = 0.015
- q_vel = 0.3
- 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)
-
- q_pos_ff = 0.005
- q_vel_ff = 1.0
- self.Qff = numpy.matrix([[(1.0 / (q_pos_ff ** 2.0)), 0.0],
- [0.0, (1.0 / (q_vel_ff ** 2.0))]])
-
- self.Kff = controls.TwoStateFeedForwards(self.B, self.Qff)
-
- glog.debug('K %s', repr(self.K))
- glog.debug('Poles are %s',
- repr(numpy.linalg.eig(self.A - self.B * self.K)[0]))
-
- q_pos = 0.10
- q_vel = 1.65
- 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)
-
- glog.debug('Kal %s', repr(self.KalmanGain))
- self.L = self.A * self.KalmanGain
- glog.debug('KalL is %s', repr(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 IntegralIntake(Intake):
- def __init__(self, name='IntegralIntake'):
- super(IntegralIntake, self).__init__(name=name)
-
- 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 = 0.12
- q_vel = 2.00
- q_voltage = 40.0
- 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.Kff = numpy.concatenate((self.Kff, numpy.matrix(numpy.zeros((1, 1)))), axis=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 = []
- self.offset = []
-
- def run_test(self, intake, end_goal,
- controller_intake,
- observer_intake=None,
- iterations=200):
- """Runs the intake plant with an initial condition and goal.
-
- Args:
- intake: intake object to use.
- end_goal: end_goal state.
- controller_intake: Intake object to get K from, or None if we should
- use intake.
- observer_intake: Intake object to use for the observer, or None if we should
- use the actual state.
- iterations: Number of timesteps to run the model for.
- """
-
- if controller_intake is None:
- controller_intake = intake
-
- vbat = 12.0
-
- if self.t:
- initial_t = self.t[-1] + intake.dt
- else:
- initial_t = 0
-
- goal = numpy.concatenate((intake.X, numpy.matrix(numpy.zeros((1, 1)))), axis=0)
-
- profile = TrapezoidProfile(intake.dt)
- profile.set_maximum_acceleration(10.0)
- profile.set_maximum_velocity(0.3)
- profile.SetGoal(goal[0, 0])
-
- U_last = numpy.matrix(numpy.zeros((1, 1)))
- for i in xrange(iterations):
- observer_intake.Y = intake.Y
- observer_intake.CorrectObserver(U_last)
-
- self.offset.append(observer_intake.X_hat[2, 0])
- self.x_hat.append(observer_intake.X_hat[0, 0])
-
- next_goal = numpy.concatenate(
- (profile.Update(end_goal[0, 0], end_goal[1, 0]),
- numpy.matrix(numpy.zeros((1, 1)))),
- axis=0)
-
- ff_U = controller_intake.Kff * (next_goal - observer_intake.A * goal)
-
- U_uncapped = controller_intake.K * (goal - observer_intake.X_hat) + ff_U
- U_uncapped = controller_intake.K * (end_goal - observer_intake.X_hat)
- U = U_uncapped.copy()
- U[0, 0] = numpy.clip(U[0, 0], -vbat, vbat)
- self.x.append(intake.X[0, 0])
-
- if self.v:
- last_v = self.v[-1]
- else:
- last_v = 0
-
- self.v.append(intake.X[1, 0])
- self.a.append((self.v[-1] - last_v) / intake.dt)
-
- offset = 0.0
- if i > 100:
- offset = 2.0
- intake.Update(U + offset)
-
- observer_intake.PredictObserver(U)
-
- self.t.append(initial_t + i * intake.dt)
- self.u.append(U[0, 0])
-
- ff_U -= U_uncapped - U
- goal = controller_intake.A * goal + controller_intake.B * ff_U
-
- if U[0, 0] != U_uncapped[0, 0]:
- profile.MoveCurrentState(
- numpy.matrix([[goal[0, 0]], [goal[1, 0]]]))
-
- glog.debug('Time: %f', self.t[-1])
- glog.debug('goal_error %s', repr(end_goal - goal))
- glog.debug('error %s', repr(observer_intake.X_hat - end_goal))
-
- 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.plot(self.t, self.offset, label='voltage_offset')
- pylab.legend()
-
- pylab.subplot(3, 1, 3)
- pylab.plot(self.t, self.a, label='a')
- pylab.legend()
-
- pylab.show()
+ G=(1.0 / 35.0) * (20.0 / 40.0),
+ radius=16.0 * 0.25 / (2.0 * numpy.pi) * 0.0254,
+ mass=5.4,
+ q_pos=0.015,
+ q_vel=0.3,
+ kalman_q_pos=0.12,
+ kalman_q_vel=2.00,
+ kalman_q_voltage=40.0,
+ kalman_r_position=0.05)
def main(argv):
- scenario_plotter = ScenarioPlotter()
+ if FLAGS.plot:
+ R = numpy.matrix([[0.1], [0.0]])
+ linear_system.PlotMotion(kIntake, R)
- intake = Intake()
- intake_controller = IntegralIntake()
- observer_intake = IntegralIntake()
+ # Write the generated constants out to a file.
+ if len(argv) != 5:
+ glog.fatal(
+ 'Expected .h file name and .cc file name for the intake and integral intake.'
+ )
+ else:
+ namespaces = ['y2017', 'control_loops', 'superstructure', 'intake']
+ linear_system.WriteLinearSystem(kIntake, argv[1:3], argv[3:5],
+ namespaces)
- # Test moving the intake with constant separation.
- initial_X = numpy.matrix([[0.0], [0.0]])
- R = numpy.matrix([[0.1], [0.0], [0.0]])
- scenario_plotter.run_test(intake, end_goal=R,
- controller_intake=intake_controller,
- observer_intake=observer_intake, iterations=400)
-
- if FLAGS.plot:
- scenario_plotter.Plot()
-
- # Write the generated constants out to a file.
- if len(argv) != 5:
- glog.fatal('Expected .h file name and .cc file name for the intake and integral intake.')
- else:
- namespaces = ['y2017', 'control_loops', 'superstructure', 'intake']
- intake = Intake('Intake')
- loop_writer = control_loop.ControlLoopWriter('Intake', [intake],
- namespaces=namespaces)
- loop_writer.AddConstant(control_loop.Constant('kFreeSpeed', '%f',
- intake.free_speed))
- loop_writer.AddConstant(control_loop.Constant('kOutputRatio', '%f',
- intake.G * intake.r))
- loop_writer.Write(argv[1], argv[2])
-
- integral_intake = IntegralIntake('IntegralIntake')
- integral_loop_writer = control_loop.ControlLoopWriter('IntegralIntake', [integral_intake],
- namespaces=namespaces)
- integral_loop_writer.Write(argv[3], argv[4])
if __name__ == '__main__':
- argv = FLAGS(sys.argv)
- glog.init()
- sys.exit(main(argv))
+ argv = FLAGS(sys.argv)
+ glog.init()
+ sys.exit(main(argv))