blob: 5665fd9412a4afa630fd9b944b553611a81b0fb5 [file] [log] [blame]
#!/usr/bin/python
from frc971.control_loops.python import control_loop
from frc971.control_loops.python import controls
import numpy
import sys
from matplotlib import pylab
import glog
class DrivetrainParams(object):
def __init__(self, J, mass, robot_radius, wheel_radius, G_high, G_low,
q_pos_low, q_pos_high, q_vel_low, q_vel_high,
motor_type = control_loop.CIM(), num_motors = 2, dt = 0.00505,
controller_poles=[0.90, 0.90], observer_poles=[0.02, 0.02]):
"""Defines all constants of a drivetrain.
Args:
J: float, Moment of inertia of drivetrain in kg m^2
mass: float, Mass of the robot in kg.
robot_radius: float, Radius of the robot, in meters (requires tuning by
hand).
wheel_radius: float, Radius of the wheels, in meters.
G_high: float, Gear ratio for high gear.
G_low: float, Gear ratio for low gear.
dt: float, Control loop time step.
q_pos_low: float, q position low gear.
q_pos_high: float, q position high gear.
q_vel_low: float, q velocity low gear.
q_vel_high: float, q velocity high gear.
motor_type: object, class of values defining the motor in drivetrain.
num_motors: int, number of motors on one side of drivetrain.
controller_poles: array, An array of poles. (See control_loop.py)
observer_poles: array, An array of poles. (See control_loop.py)
"""
self.J = J
self.mass = mass
self.robot_radius = robot_radius
self.wheel_radius = wheel_radius
self.G_high = G_high
self.G_low = G_low
self.dt = dt
self.q_pos_low = q_pos_low
self.q_pos_high = q_pos_high
self.q_vel_low = q_vel_low
self.q_vel_high = q_vel_high
self.motor_type = motor_type
self.num_motors = num_motors
self.controller_poles = controller_poles
self.observer_poles = observer_poles
class Drivetrain(control_loop.ControlLoop):
def __init__(self, drivetrain_params, name="Drivetrain", left_low=True,
right_low=True):
"""Defines a base drivetrain for a robot.
Args:
drivetrain_params: DrivetrainParams, class of values defining the drivetrain.
name: string, Name of this drivetrain.
left_low: bool, Whether the left is in high gear.
right_low: bool, Whether the right is in high gear.
"""
super(Drivetrain, self).__init__(name)
# Moment of inertia of the drivetrain in kg m^2
self.J = drivetrain_params.J
# Mass of the robot, in kg.
self.mass = drivetrain_params.mass
# Radius of the robot, in meters (requires tuning by hand)
self.robot_radius = drivetrain_params.robot_radius
# Radius of the wheels, in meters.
self.r = drivetrain_params.wheel_radius
# Gear ratios
self.G_low = drivetrain_params.G_low
self.G_high = drivetrain_params.G_high
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 = drivetrain_params.dt
self.BuildDrivetrain(drivetrain_params.motor_type, drivetrain_params.num_motors);
if left_low or right_low:
q_pos = drivetrain_params.q_pos_low
q_vel = drivetrain_params.q_vel_low
else:
q_pos = drivetrain_params.q_pos_high
q_vel = drivetrain_params.q_vel_high
self.BuildDrivetrainController(q_pos, q_vel)
self.InitializeState()
def BuildDrivetrain(self, motor, num_motors_per_side):
self.motor = motor
# Number of motors per side
self.num_motors = num_motors_per_side
# Stall Torque in N m
self.stall_torque = motor.stall_torque * self.num_motors * 0.60
# Stall Current in Amps
self.stall_current = motor.stall_current * self.num_motors
# Free Speed in rad/s
self.free_speed = motor.free_speed
# Free Current in Amps
self.free_current = motor.free_current * self.num_motors
# Effective motor resistance in ohms.
self.resistance = 12.0 / self.stall_current
# Resistance of the motor, divided by the number of motors.
# Motor velocity constant
self.Kv = (self.free_speed / (12.0 - self.resistance * self.free_current))
# Torque constant
self.Kt = self.stall_torque / self.stall_current
# 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.mass + self.robot_radius * self.robot_radius / self.J
self.msn = 1.0 / self.mass - self.robot_radius * self.robot_radius / self.J
# The calculations which we will need for A and B.
self.tcl = self.Kt / self.Kv / (self.Gl * self.Gl * self.resistance * self.r * self.r)
self.tcr = self.Kt / self.Kv / (self.Gr * self.Gr * self.resistance * self.r * self.r)
self.mpl = self.Kt / (self.Gl * self.resistance * self.r)
self.mpr = self.Kt / (self.Gr * self.resistance * 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]])
self.A, self.B = self.ContinuousToDiscrete(
self.A_continuous, self.B_continuous, self.dt)
def BuildDrivetrainController(self, q_pos, q_vel):
# Tune the LQR controller
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)
glog.debug('DT q_pos %f q_vel %s %s', q_pos, q_vel, self._name)
glog.debug(str(numpy.linalg.eig(self.A - self.B * self.K)[0]))
glog.debug('K %s', repr(self.K))
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]])
class KFDrivetrain(Drivetrain):
def __init__(self, drivetrain_params, name="KFDrivetrain",
left_low=True, right_low=True):
"""Kalman filter values of a drivetrain.
Args:
drivetrain_params: DrivetrainParams, class of values defining the drivetrain.
name: string, Name of this drivetrain.
left_low: bool, Whether the left is in high gear.
right_low: bool, Whether the right is in high gear.
"""
super(KFDrivetrain, self).__init__(drivetrain_params, name, left_low, right_low)
self.unaugmented_A_continuous = self.A_continuous
self.unaugmented_B_continuous = self.B_continuous
# The practical voltage applied to the wheels is
# V_left = U_left + left_voltage_error
#
# The states are
# [left position, left velocity, right position, right velocity,
# left voltage error, right voltage error, angular_error]
#
# The left and right positions are filtered encoder positions and are not
# adjusted for heading error.
# The turn velocity as computed by the left and right velocities is
# adjusted by the gyro velocity.
# The angular_error is the angular velocity error between the wheel speed
# and the gyro speed.
self.A_continuous = numpy.matrix(numpy.zeros((7, 7)))
self.B_continuous = numpy.matrix(numpy.zeros((7, 2)))
self.A_continuous[0:4,0:4] = self.unaugmented_A_continuous
self.A_continuous[0:4,4:6] = self.unaugmented_B_continuous
self.B_continuous[0:4,0:2] = self.unaugmented_B_continuous
self.A_continuous[0,6] = 1
self.A_continuous[2,6] = -1
self.A, self.B = self.ContinuousToDiscrete(
self.A_continuous, self.B_continuous, self.dt)
self.C = numpy.matrix([[1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[0, -0.5 / drivetrain_params.robot_radius, 0, 0.5 / drivetrain_params.robot_radius, 0, 0, 0]])
self.D = numpy.matrix([[0, 0],
[0, 0],
[0, 0]])
q_pos = 0.05
q_vel = 1.00
q_voltage = 10.0
q_encoder_uncertainty = 2.00
self.Q = numpy.matrix([[(q_pos ** 2.0), 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, (q_vel ** 2.0), 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, (q_pos ** 2.0), 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, (q_vel ** 2.0), 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, (q_voltage ** 2.0), 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, (q_voltage ** 2.0), 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, (q_encoder_uncertainty ** 2.0)]])
r_pos = 0.0001
r_gyro = 0.000001
self.R = numpy.matrix([[(r_pos ** 2.0), 0.0, 0.0],
[0.0, (r_pos ** 2.0), 0.0],
[0.0, 0.0, (r_gyro ** 2.0)]])
# Solving for kf gains.
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
unaug_K = self.K
# Implement a nice closed loop controller for use by the closed loop
# controller.
self.K = numpy.matrix(numpy.zeros((self.B.shape[1], self.A.shape[0])))
self.K[0:2, 0:4] = unaug_K
self.K[0, 4] = 1.0
self.K[1, 5] = 1.0
self.Qff = numpy.matrix(numpy.zeros((4, 4)))
qff_pos = 0.005
qff_vel = 1.00
self.Qff[0, 0] = 1.0 / qff_pos ** 2.0
self.Qff[1, 1] = 1.0 / qff_vel ** 2.0
self.Qff[2, 2] = 1.0 / qff_pos ** 2.0
self.Qff[3, 3] = 1.0 / qff_vel ** 2.0
self.Kff = numpy.matrix(numpy.zeros((2, 7)))
self.Kff[0:2, 0:4] = controls.TwoStateFeedForwards(self.B[0:4,:], self.Qff)
self.InitializeState()
def WriteDrivetrain(drivetrain_files, kf_drivetrain_files, year_namespace,
drivetrain_params):
# Write the generated constants out to a file.
drivetrain_low_low = Drivetrain(name="DrivetrainLowLow",
left_low=True, right_low=True, drivetrain_params=drivetrain_params)
drivetrain_low_high = Drivetrain(name="DrivetrainLowHigh",
left_low=True, right_low=False, drivetrain_params=drivetrain_params)
drivetrain_high_low = Drivetrain(name="DrivetrainHighLow",
left_low=False, right_low=True, drivetrain_params=drivetrain_params)
drivetrain_high_high = Drivetrain(name="DrivetrainHighHigh",
left_low=False, right_low=False, drivetrain_params=drivetrain_params)
kf_drivetrain_low_low = KFDrivetrain(name="KFDrivetrainLowLow",
left_low=True, right_low=True, drivetrain_params=drivetrain_params)
kf_drivetrain_low_high = KFDrivetrain(name="KFDrivetrainLowHigh",
left_low=True, right_low=False, drivetrain_params=drivetrain_params)
kf_drivetrain_high_low = KFDrivetrain(name="KFDrivetrainHighLow",
left_low=False, right_low=True, drivetrain_params=drivetrain_params)
kf_drivetrain_high_high = KFDrivetrain(name="KFDrivetrainHighHigh",
left_low=False, right_low=False, drivetrain_params=drivetrain_params)
namespaces = [year_namespace, 'control_loops', 'drivetrain']
dog_loop_writer = control_loop.ControlLoopWriter(
"Drivetrain", [drivetrain_low_low, drivetrain_low_high,
drivetrain_high_low, drivetrain_high_high],
namespaces = namespaces)
dog_loop_writer.AddConstant(control_loop.Constant("kDt", "%f",
drivetrain_low_low.dt))
dog_loop_writer.AddConstant(control_loop.Constant("kStallTorque", "%f",
drivetrain_low_low.stall_torque))
dog_loop_writer.AddConstant(control_loop.Constant("kStallCurrent", "%f",
drivetrain_low_low.stall_current))
dog_loop_writer.AddConstant(control_loop.Constant("kFreeSpeed", "%f",
drivetrain_low_low.free_speed))
dog_loop_writer.AddConstant(control_loop.Constant("kFreeCurrent", "%f",
drivetrain_low_low.free_current))
dog_loop_writer.AddConstant(control_loop.Constant("kJ", "%f",
drivetrain_low_low.J))
dog_loop_writer.AddConstant(control_loop.Constant("kMass", "%f",
drivetrain_low_low.mass))
dog_loop_writer.AddConstant(control_loop.Constant("kRobotRadius", "%f",
drivetrain_low_low.robot_radius))
dog_loop_writer.AddConstant(control_loop.Constant("kWheelRadius", "%f",
drivetrain_low_low.r))
dog_loop_writer.AddConstant(control_loop.Constant("kR", "%f",
drivetrain_low_low.resistance))
dog_loop_writer.AddConstant(control_loop.Constant("kV", "%f",
drivetrain_low_low.Kv))
dog_loop_writer.AddConstant(control_loop.Constant("kT", "%f",
drivetrain_low_low.Kt))
dog_loop_writer.AddConstant(control_loop.Constant("kLowGearRatio", "%f",
drivetrain_low_low.G_low))
dog_loop_writer.AddConstant(control_loop.Constant("kHighGearRatio", "%f",
drivetrain_high_high.G_high))
dog_loop_writer.AddConstant(control_loop.Constant("kHighOutputRatio", "%f",
drivetrain_high_high.G_high * drivetrain_high_high.r))
dog_loop_writer.Write(drivetrain_files[0], drivetrain_files[1])
kf_loop_writer = control_loop.ControlLoopWriter(
"KFDrivetrain", [kf_drivetrain_low_low, kf_drivetrain_low_high,
kf_drivetrain_high_low, kf_drivetrain_high_high],
namespaces = namespaces)
kf_loop_writer.Write(kf_drivetrain_files[0], kf_drivetrain_files[1])
def PlotDrivetrainMotions(drivetrain_params):
# Simulate the response of the system to a step input.
drivetrain = Drivetrain(left_low=False, right_low=False, drivetrain_params=drivetrain_params)
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.rc('lines', linewidth=4)
pylab.plot(range(100), simulated_left, label='left position')
pylab.plot(range(100), simulated_right, 'r--', label='right position')
pylab.suptitle('Acceleration Test\n12 Volt Step Input')
pylab.legend(loc='lower right')
pylab.show()
# Simulate forwards motion.
drivetrain = Drivetrain(left_low=False, right_low=False, drivetrain_params=drivetrain_params)
close_loop_left = []
close_loop_right = []
left_power = []
right_power = []
R = numpy.matrix([[1.0], [0.0], [1.0], [0.0]])
for _ in xrange(300):
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])
left_power.append(U[0, 0])
right_power.append(U[1, 0])
pylab.plot(range(300), close_loop_left, label='left position')
pylab.plot(range(300), close_loop_right, 'm--', label='right position')
pylab.plot(range(300), left_power, label='left power')
pylab.plot(range(300), right_power, '--', label='right power')
pylab.suptitle('Linear Move\nLeft and Right Position going to 1')
pylab.legend()
pylab.show()
# Try turning in place
drivetrain = Drivetrain(drivetrain_params=drivetrain_params)
close_loop_left = []
close_loop_right = []
R = numpy.matrix([[-1.0], [0.0], [1.0], [0.0]])
for _ in xrange(200):
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(200), close_loop_left, label='left position')
pylab.plot(range(200), close_loop_right, label='right position')
pylab.suptitle('Angular Move\nLeft position going to -1 and right position going to 1')
pylab.legend(loc='center right')
pylab.show()
# Try turning just one side.
drivetrain = Drivetrain(drivetrain_params=drivetrain_params)
close_loop_left = []
close_loop_right = []
R = numpy.matrix([[0.0], [0.0], [1.0], [0.0]])
for _ in xrange(300):
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(300), close_loop_left, label='left position')
pylab.plot(range(300), close_loop_right, label='right position')
pylab.suptitle('Pivot\nLeft position not changing and right position going to 1')
pylab.legend(loc='center right')
pylab.show()