| #!/usr/bin/python |
| |
| import numpy |
| import sys |
| from frc971.control_loops.python import polytope |
| from y2014.control_loops.python import drivetrain |
| from frc971.control_loops.python import control_loop |
| from frc971.control_loops.python import controls |
| from matplotlib import pylab |
| |
| __author__ = 'Austin Schuh (austin.linux@gmail.com)' |
| |
| |
| def CoerceGoal(region, K, w, R): |
| """Intersects a line with a region, and finds the closest point to R. |
| |
| Finds a point that is closest to R inside the region, and on the line |
| defined by K X = w. If it is not possible to find a point on the line, |
| finds a point that is inside the region and closest to the line. This |
| function assumes that |
| |
| Args: |
| region: HPolytope, the valid goal region. |
| K: numpy.matrix (2 x 1), the matrix for the equation [K1, K2] [x1; x2] = w |
| w: float, the offset in the equation above. |
| R: numpy.matrix (2 x 1), the point to be closest to. |
| |
| Returns: |
| numpy.matrix (2 x 1), the point. |
| """ |
| return DoCoerceGoal(region, K, w, R)[0] |
| |
| def DoCoerceGoal(region, K, w, R): |
| if region.IsInside(R): |
| return (R, True) |
| |
| perpendicular_vector = K.T / numpy.linalg.norm(K) |
| parallel_vector = numpy.matrix([[perpendicular_vector[1, 0]], |
| [-perpendicular_vector[0, 0]]]) |
| |
| # We want to impose the constraint K * X = w on the polytope H * X <= k. |
| # We do this by breaking X up into parallel and perpendicular components to |
| # the half plane. This gives us the following equation. |
| # |
| # parallel * (parallel.T \dot X) + perpendicular * (perpendicular \dot X)) = X |
| # |
| # Then, substitute this into the polytope. |
| # |
| # H * (parallel * (parallel.T \dot X) + perpendicular * (perpendicular \dot X)) <= k |
| # |
| # Substitute K * X = w |
| # |
| # H * parallel * (parallel.T \dot X) + H * perpendicular * w <= k |
| # |
| # Move all the knowns to the right side. |
| # |
| # H * parallel * ([parallel1 parallel2] * X) <= k - H * perpendicular * w |
| # |
| # Let t = parallel.T \dot X, the component parallel to the surface. |
| # |
| # H * parallel * t <= k - H * perpendicular * w |
| # |
| # This is a polytope which we can solve, and use to figure out the range of X |
| # that we care about! |
| |
| t_poly = polytope.HPolytope( |
| region.H * parallel_vector, |
| region.k - region.H * perpendicular_vector * w) |
| |
| vertices = t_poly.Vertices() |
| |
| if vertices.shape[0]: |
| # The region exists! |
| # Find the closest vertex |
| min_distance = numpy.infty |
| closest_point = None |
| for vertex in vertices: |
| point = parallel_vector * vertex + perpendicular_vector * w |
| length = numpy.linalg.norm(R - point) |
| if length < min_distance: |
| min_distance = length |
| closest_point = point |
| |
| return (closest_point, True) |
| else: |
| # Find the vertex of the space that is closest to the line. |
| region_vertices = region.Vertices() |
| min_distance = numpy.infty |
| closest_point = None |
| for vertex in region_vertices: |
| point = vertex.T |
| length = numpy.abs((perpendicular_vector.T * point)[0, 0]) |
| if length < min_distance: |
| min_distance = length |
| closest_point = point |
| |
| return (closest_point, False) |
| |
| |
| class VelocityDrivetrainModel(control_loop.ControlLoop): |
| def __init__(self, left_low=True, right_low=True, name="VelocityDrivetrainModel"): |
| super(VelocityDrivetrainModel, self).__init__(name) |
| self._drivetrain = drivetrain.Drivetrain(left_low=left_low, |
| right_low=right_low) |
| self.dt = 0.01 |
| self.A_continuous = numpy.matrix( |
| [[self._drivetrain.A_continuous[1, 1], self._drivetrain.A_continuous[1, 3]], |
| [self._drivetrain.A_continuous[3, 1], self._drivetrain.A_continuous[3, 3]]]) |
| |
| self.B_continuous = numpy.matrix( |
| [[self._drivetrain.B_continuous[1, 0], self._drivetrain.B_continuous[1, 1]], |
| [self._drivetrain.B_continuous[3, 0], self._drivetrain.B_continuous[3, 1]]]) |
| self.C = numpy.matrix(numpy.eye(2)); |
| self.D = numpy.matrix(numpy.zeros((2, 2))); |
| |
| self.A, self.B = self.ContinuousToDiscrete(self.A_continuous, |
| self.B_continuous, self.dt) |
| |
| # FF * X = U (steady state) |
| self.FF = self.B.I * (numpy.eye(2) - self.A) |
| |
| self.PlaceControllerPoles([0.6, 0.6]) |
| self.PlaceObserverPoles([0.02, 0.02]) |
| |
| self.G_high = self._drivetrain.G_high |
| self.G_low = self._drivetrain.G_low |
| self.R = self._drivetrain.R |
| self.r = self._drivetrain.r |
| self.Kv = self._drivetrain.Kv |
| self.Kt = self._drivetrain.Kt |
| |
| self.U_max = self._drivetrain.U_max |
| self.U_min = self._drivetrain.U_min |
| |
| |
| class VelocityDrivetrain(object): |
| HIGH = 'high' |
| LOW = 'low' |
| SHIFTING_UP = 'up' |
| SHIFTING_DOWN = 'down' |
| |
| def __init__(self): |
| self.drivetrain_low_low = VelocityDrivetrainModel( |
| left_low=True, right_low=True, name='VelocityDrivetrainLowLow') |
| self.drivetrain_low_high = VelocityDrivetrainModel(left_low=True, right_low=False, name='VelocityDrivetrainLowHigh') |
| self.drivetrain_high_low = VelocityDrivetrainModel(left_low=False, right_low=True, name = 'VelocityDrivetrainHighLow') |
| self.drivetrain_high_high = VelocityDrivetrainModel(left_low=False, right_low=False, name = 'VelocityDrivetrainHighHigh') |
| |
| # X is [lvel, rvel] |
| self.X = numpy.matrix( |
| [[0.0], |
| [0.0]]) |
| |
| self.U_poly = polytope.HPolytope( |
| numpy.matrix([[1, 0], |
| [-1, 0], |
| [0, 1], |
| [0, -1]]), |
| numpy.matrix([[12], |
| [12], |
| [12], |
| [12]])) |
| |
| self.U_max = numpy.matrix( |
| [[12.0], |
| [12.0]]) |
| self.U_min = numpy.matrix( |
| [[-12.0000000000], |
| [-12.0000000000]]) |
| |
| self.dt = 0.01 |
| |
| self.R = numpy.matrix( |
| [[0.0], |
| [0.0]]) |
| |
| # ttrust is the comprimise between having full throttle negative inertia, |
| # and having no throttle negative inertia. A value of 0 is full throttle |
| # inertia. A value of 1 is no throttle negative inertia. |
| self.ttrust = 1.0 |
| |
| self.left_gear = VelocityDrivetrain.LOW |
| self.right_gear = VelocityDrivetrain.LOW |
| self.left_shifter_position = 0.0 |
| self.right_shifter_position = 0.0 |
| self.left_cim = drivetrain.CIM() |
| self.right_cim = drivetrain.CIM() |
| |
| def IsInGear(self, gear): |
| return gear is VelocityDrivetrain.HIGH or gear is VelocityDrivetrain.LOW |
| |
| def MotorRPM(self, shifter_position, velocity): |
| if shifter_position > 0.5: |
| return (velocity / self.CurrentDrivetrain().G_high / |
| self.CurrentDrivetrain().r) |
| else: |
| return (velocity / self.CurrentDrivetrain().G_low / |
| self.CurrentDrivetrain().r) |
| |
| def CurrentDrivetrain(self): |
| if self.left_shifter_position > 0.5: |
| if self.right_shifter_position > 0.5: |
| return self.drivetrain_high_high |
| else: |
| return self.drivetrain_high_low |
| else: |
| if self.right_shifter_position > 0.5: |
| return self.drivetrain_low_high |
| else: |
| return self.drivetrain_low_low |
| |
| def SimShifter(self, gear, shifter_position): |
| if gear is VelocityDrivetrain.HIGH or gear is VelocityDrivetrain.SHIFTING_UP: |
| shifter_position = min(shifter_position + 0.5, 1.0) |
| else: |
| shifter_position = max(shifter_position - 0.5, 0.0) |
| |
| if shifter_position == 1.0: |
| gear = VelocityDrivetrain.HIGH |
| elif shifter_position == 0.0: |
| gear = VelocityDrivetrain.LOW |
| |
| return gear, shifter_position |
| |
| def ComputeGear(self, wheel_velocity, should_print=False, current_gear=False, gear_name=None): |
| high_omega = (wheel_velocity / self.CurrentDrivetrain().G_high / |
| self.CurrentDrivetrain().r) |
| low_omega = (wheel_velocity / self.CurrentDrivetrain().G_low / |
| self.CurrentDrivetrain().r) |
| #print gear_name, "Motor Energy Difference.", 0.5 * 0.000140032647 * (low_omega * low_omega - high_omega * high_omega), "joules" |
| high_torque = ((12.0 - high_omega / self.CurrentDrivetrain().Kv) * |
| self.CurrentDrivetrain().Kt / self.CurrentDrivetrain().R) |
| low_torque = ((12.0 - low_omega / self.CurrentDrivetrain().Kv) * |
| self.CurrentDrivetrain().Kt / self.CurrentDrivetrain().R) |
| high_power = high_torque * high_omega |
| low_power = low_torque * low_omega |
| #if should_print: |
| # print gear_name, "High omega", high_omega, "Low omega", low_omega |
| # print gear_name, "High torque", high_torque, "Low torque", low_torque |
| # print gear_name, "High power", high_power, "Low power", low_power |
| |
| # Shift algorithm improvements. |
| # TODO(aschuh): |
| # It takes time to shift. Shifting down for 1 cycle doesn't make sense |
| # because you will end up slower than without shifting. Figure out how |
| # to include that info. |
| # If the driver is still in high gear, but isn't asking for the extra power |
| # from low gear, don't shift until he asks for it. |
| goal_gear_is_high = high_power > low_power |
| #goal_gear_is_high = True |
| |
| if not self.IsInGear(current_gear): |
| print gear_name, 'Not in gear.' |
| return current_gear |
| else: |
| is_high = current_gear is VelocityDrivetrain.HIGH |
| if is_high != goal_gear_is_high: |
| if goal_gear_is_high: |
| print gear_name, 'Shifting up.' |
| return VelocityDrivetrain.SHIFTING_UP |
| else: |
| print gear_name, 'Shifting down.' |
| return VelocityDrivetrain.SHIFTING_DOWN |
| else: |
| return current_gear |
| |
| def FilterVelocity(self, throttle): |
| # Invert the plant to figure out how the velocity filter would have to work |
| # out in order to filter out the forwards negative inertia. |
| # This math assumes that the left and right power and velocity are equal. |
| |
| # The throttle filter should filter such that the motor in the highest gear |
| # should be controlling the time constant. |
| # Do this by finding the index of FF that has the lowest value, and computing |
| # the sums using that index. |
| FF_sum = self.CurrentDrivetrain().FF.sum(axis=1) |
| min_FF_sum_index = numpy.argmin(FF_sum) |
| min_FF_sum = FF_sum[min_FF_sum_index, 0] |
| min_K_sum = self.CurrentDrivetrain().K[min_FF_sum_index, :].sum() |
| # Compute the FF sum for high gear. |
| high_min_FF_sum = self.drivetrain_high_high.FF[0, :].sum() |
| |
| # U = self.K[0, :].sum() * (R - x_avg) + self.FF[0, :].sum() * R |
| # throttle * 12.0 = (self.K[0, :].sum() + self.FF[0, :].sum()) * R |
| # - self.K[0, :].sum() * x_avg |
| |
| # R = (throttle * 12.0 + self.K[0, :].sum() * x_avg) / |
| # (self.K[0, :].sum() + self.FF[0, :].sum()) |
| |
| # U = (K + FF) * R - K * X |
| # (K + FF) ^-1 * (U + K * X) = R |
| |
| # Scale throttle by min_FF_sum / high_min_FF_sum. This will make low gear |
| # have the same velocity goal as high gear, and so that the robot will hold |
| # the same speed for the same throttle for all gears. |
| adjusted_ff_voltage = numpy.clip(throttle * 12.0 * min_FF_sum / high_min_FF_sum, -12.0, 12.0) |
| return ((adjusted_ff_voltage + self.ttrust * min_K_sum * (self.X[0, 0] + self.X[1, 0]) / 2.0) |
| / (self.ttrust * min_K_sum + min_FF_sum)) |
| |
| def Update(self, throttle, steering): |
| # Shift into the gear which sends the most power to the floor. |
| # This is the same as sending the most torque down to the floor at the |
| # wheel. |
| |
| self.left_gear = self.right_gear = True |
| if True: |
| self.left_gear = self.ComputeGear(self.X[0, 0], should_print=True, |
| current_gear=self.left_gear, |
| gear_name="left") |
| self.right_gear = self.ComputeGear(self.X[1, 0], should_print=True, |
| current_gear=self.right_gear, |
| gear_name="right") |
| if self.IsInGear(self.left_gear): |
| self.left_cim.X[0, 0] = self.MotorRPM(self.left_shifter_position, self.X[0, 0]) |
| |
| if self.IsInGear(self.right_gear): |
| self.right_cim.X[0, 0] = self.MotorRPM(self.right_shifter_position, self.X[0, 0]) |
| |
| if self.IsInGear(self.left_gear) and self.IsInGear(self.right_gear): |
| # Filter the throttle to provide a nicer response. |
| fvel = self.FilterVelocity(throttle) |
| |
| # Constant radius means that angualar_velocity / linear_velocity = constant. |
| # Compute the left and right velocities. |
| steering_velocity = numpy.abs(fvel) * steering |
| left_velocity = fvel - steering_velocity |
| right_velocity = fvel + steering_velocity |
| |
| # Write this constraint in the form of K * R = w |
| # angular velocity / linear velocity = constant |
| # (left - right) / (left + right) = constant |
| # left - right = constant * left + constant * right |
| |
| # (fvel - steering * numpy.abs(fvel) - fvel - steering * numpy.abs(fvel)) / |
| # (fvel - steering * numpy.abs(fvel) + fvel + steering * numpy.abs(fvel)) = |
| # constant |
| # (- 2 * steering * numpy.abs(fvel)) / (2 * fvel) = constant |
| # (-steering * sign(fvel)) = constant |
| # (-steering * sign(fvel)) * (left + right) = left - right |
| # (steering * sign(fvel) + 1) * left + (steering * sign(fvel) - 1) * right = 0 |
| |
| equality_k = numpy.matrix( |
| [[1 + steering * numpy.sign(fvel), -(1 - steering * numpy.sign(fvel))]]) |
| equality_w = 0.0 |
| |
| self.R[0, 0] = left_velocity |
| self.R[1, 0] = right_velocity |
| |
| # Construct a constraint on R by manipulating the constraint on U |
| # Start out with H * U <= k |
| # U = FF * R + K * (R - X) |
| # H * (FF * R + K * R - K * X) <= k |
| # H * (FF + K) * R <= k + H * K * X |
| R_poly = polytope.HPolytope( |
| self.U_poly.H * (self.CurrentDrivetrain().K + self.CurrentDrivetrain().FF), |
| self.U_poly.k + self.U_poly.H * self.CurrentDrivetrain().K * self.X) |
| |
| # Limit R back inside the box. |
| self.boxed_R = CoerceGoal(R_poly, equality_k, equality_w, self.R) |
| |
| FF_volts = self.CurrentDrivetrain().FF * self.boxed_R |
| self.U_ideal = self.CurrentDrivetrain().K * (self.boxed_R - self.X) + FF_volts |
| else: |
| print 'Not all in gear' |
| if not self.IsInGear(self.left_gear) and not self.IsInGear(self.right_gear): |
| # TODO(austin): Use battery volts here. |
| R_left = self.MotorRPM(self.left_shifter_position, self.X[0, 0]) |
| self.U_ideal[0, 0] = numpy.clip( |
| self.left_cim.K * (R_left - self.left_cim.X) + R_left / self.left_cim.Kv, |
| self.left_cim.U_min, self.left_cim.U_max) |
| self.left_cim.Update(self.U_ideal[0, 0]) |
| |
| R_right = self.MotorRPM(self.right_shifter_position, self.X[1, 0]) |
| self.U_ideal[1, 0] = numpy.clip( |
| self.right_cim.K * (R_right - self.right_cim.X) + R_right / self.right_cim.Kv, |
| self.right_cim.U_min, self.right_cim.U_max) |
| self.right_cim.Update(self.U_ideal[1, 0]) |
| else: |
| assert False |
| |
| self.U = numpy.clip(self.U_ideal, self.U_min, self.U_max) |
| |
| # TODO(austin): Model the robot as not accelerating when you shift... |
| # This hack only works when you shift at the same time. |
| if self.IsInGear(self.left_gear) and self.IsInGear(self.right_gear): |
| self.X = self.CurrentDrivetrain().A * self.X + self.CurrentDrivetrain().B * self.U |
| |
| self.left_gear, self.left_shifter_position = self.SimShifter( |
| self.left_gear, self.left_shifter_position) |
| self.right_gear, self.right_shifter_position = self.SimShifter( |
| self.right_gear, self.right_shifter_position) |
| |
| print "U is", self.U[0, 0], self.U[1, 0] |
| print "Left shifter", self.left_gear, self.left_shifter_position, "Right shifter", self.right_gear, self.right_shifter_position |
| |
| |
| def main(argv): |
| vdrivetrain = VelocityDrivetrain() |
| |
| if len(argv) != 7: |
| print "Expected .h file name and .cc file name" |
| else: |
| dog_loop_writer = control_loop.ControlLoopWriter( |
| "VelocityDrivetrain", [vdrivetrain.drivetrain_low_low, |
| vdrivetrain.drivetrain_low_high, |
| vdrivetrain.drivetrain_high_low, |
| vdrivetrain.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]) |
| |
| cim_writer = control_loop.ControlLoopWriter( |
| "CIM", [drivetrain.CIM()]) |
| |
| if argv[5][-3:] == '.cc': |
| cim_writer.Write(argv[6], argv[5]) |
| else: |
| cim_writer.Write(argv[5], argv[6]) |
| return |
| |
| vl_plot = [] |
| vr_plot = [] |
| ul_plot = [] |
| ur_plot = [] |
| radius_plot = [] |
| t_plot = [] |
| left_gear_plot = [] |
| right_gear_plot = [] |
| vdrivetrain.left_shifter_position = 0.0 |
| vdrivetrain.right_shifter_position = 0.0 |
| vdrivetrain.left_gear = VelocityDrivetrain.LOW |
| vdrivetrain.right_gear = VelocityDrivetrain.LOW |
| |
| print "K is", vdrivetrain.CurrentDrivetrain().K |
| |
| if vdrivetrain.left_gear is VelocityDrivetrain.HIGH: |
| print "Left is high" |
| else: |
| print "Left is low" |
| if vdrivetrain.right_gear is VelocityDrivetrain.HIGH: |
| print "Right is high" |
| else: |
| print "Right is low" |
| |
| for t in numpy.arange(0, 1.7, vdrivetrain.dt): |
| if t < 0.5: |
| vdrivetrain.Update(throttle=0.00, steering=1.0) |
| elif t < 1.2: |
| vdrivetrain.Update(throttle=0.5, steering=1.0) |
| else: |
| vdrivetrain.Update(throttle=0.00, steering=1.0) |
| t_plot.append(t) |
| vl_plot.append(vdrivetrain.X[0, 0]) |
| vr_plot.append(vdrivetrain.X[1, 0]) |
| ul_plot.append(vdrivetrain.U[0, 0]) |
| ur_plot.append(vdrivetrain.U[1, 0]) |
| left_gear_plot.append((vdrivetrain.left_gear is VelocityDrivetrain.HIGH) * 2.0 - 10.0) |
| right_gear_plot.append((vdrivetrain.right_gear is VelocityDrivetrain.HIGH) * 2.0 - 10.0) |
| |
| fwd_velocity = (vdrivetrain.X[1, 0] + vdrivetrain.X[0, 0]) / 2 |
| turn_velocity = (vdrivetrain.X[1, 0] - vdrivetrain.X[0, 0]) |
| if abs(fwd_velocity) < 0.0000001: |
| radius_plot.append(turn_velocity) |
| else: |
| radius_plot.append(turn_velocity / fwd_velocity) |
| |
| cim_velocity_plot = [] |
| cim_voltage_plot = [] |
| cim_time = [] |
| cim = drivetrain.CIM() |
| R = numpy.matrix([[300]]) |
| for t in numpy.arange(0, 0.5, cim.dt): |
| U = numpy.clip(cim.K * (R - cim.X) + R / cim.Kv, cim.U_min, cim.U_max) |
| cim.Update(U) |
| cim_velocity_plot.append(cim.X[0, 0]) |
| cim_voltage_plot.append(U[0, 0] * 10) |
| cim_time.append(t) |
| pylab.plot(cim_time, cim_velocity_plot, label='cim spinup') |
| pylab.plot(cim_time, cim_voltage_plot, label='cim voltage') |
| pylab.legend() |
| pylab.show() |
| |
| # TODO(austin): |
| # Shifting compensation. |
| |
| # Tighten the turn. |
| # Closed loop drive. |
| |
| pylab.plot(t_plot, vl_plot, label='left velocity') |
| pylab.plot(t_plot, vr_plot, label='right velocity') |
| pylab.plot(t_plot, ul_plot, label='left voltage') |
| pylab.plot(t_plot, ur_plot, label='right voltage') |
| pylab.plot(t_plot, radius_plot, label='radius') |
| pylab.plot(t_plot, left_gear_plot, label='left gear high') |
| pylab.plot(t_plot, right_gear_plot, label='right gear high') |
| pylab.legend() |
| pylab.show() |
| return 0 |
| |
| if __name__ == '__main__': |
| sys.exit(main(sys.argv)) |