| #!/usr/bin/python3 |
| |
| from frc971.control_loops.python import control_loop |
| from frc971.control_loops.python import controls |
| 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.') |
| except gflags.DuplicateFlagError: |
| pass |
| |
| |
| class Intake(control_loop.ControlLoop): |
| |
| def __init__(self, name="Intake"): |
| super(Intake, self).__init__(name) |
| self.motor = control_loop.BAG() |
| # Stall Torque in N m |
| self.stall_torque = self.motor.stall_torque |
| # Stall Current in Amps |
| self.stall_current = self.motor.stall_current |
| # Free Speed in RPM |
| self.free_speed = self.motor.free_speed |
| # Free Current in Amps |
| self.free_current = self.motor.free_current |
| |
| # Resistance of the motor |
| self.resistance = self.motor.resistance |
| # Motor velocity constant |
| self.Kv = self.motor.Kv |
| # Torque constant |
| self.Kt = self.motor.Kt |
| # Gear ratio |
| self.G = 1.0 / 102.6 |
| |
| self.motor_inertia = 0.00000589 * 1.2 |
| |
| # Series elastic moment of inertia |
| self.Je = self.motor_inertia / (self.G * self.G) |
| # Grabber moment of inertia |
| self.Jo = 0.0363 |
| |
| # Bot has a time constant of 0.22 |
| # Current physics has a time constant of 0.18 |
| |
| # Spring constant (N m / radian) |
| self.Ks = 32.74 |
| |
| # Damper constant (N m s/ radian) |
| # 0.01 is small and 1 is big |
| self.b = 0.1 |
| |
| # Control loop time step |
| self.dt = 0.00505 |
| |
| # State is [output_position, output_velocity, |
| # elastic_position, elastic_velocity] |
| # The output position is the absolute position of the intake arm. |
| # The elastic position is the absolute position of the motor side of the |
| # series elastic. |
| # Input is [voltage] |
| |
| self.A_continuous = numpy.matrix( |
| [[0.0, 1.0, 0.0, 0.0], |
| [(-self.Ks / self.Jo), (-self.b / self.Jo), (self.Ks / self.Jo), |
| (self.b / self.Jo)], [0.0, 0.0, 0.0, 1.0], |
| [(self.Ks / self.Je), (self.b / self.Je), (-self.Ks / self.Je), |
| (-self.b / self.Je) - self.Kt / |
| (self.Je * self.resistance * self.Kv * self.G * self.G)]]) |
| |
| # Start with the unmodified input |
| self.B_continuous = numpy.matrix( |
| [[0.0], [0.0], [0.0], |
| [self.Kt / (self.G * self.Je * self.resistance)]]) |
| |
| self.C = numpy.matrix([[1.0, 0.0, -1.0, 0.0], [0.0, 0.0, 1.0, 0.0]]) |
| self.D = numpy.matrix([[0.0], [0.0]]) |
| |
| self.A, self.B = self.ContinuousToDiscrete(self.A_continuous, |
| self.B_continuous, self.dt) |
| |
| #controllability = controls.ctrb(self.A, self.B) |
| #glog.debug('ctrb: ' + repr(numpy.linalg.matrix_rank(controllability))) |
| |
| #observability = controls.ctrb(self.A.T, self.C.T) |
| #glog.debug('obs: ' + repr(numpy.linalg.matrix_rank(observability))) |
| |
| glog.debug('A_continuous ' + repr(self.A_continuous)) |
| glog.debug('B_continuous ' + repr(self.B_continuous)) |
| |
| self.K = numpy.matrix(numpy.zeros((1, 4))) |
| |
| q_pos = 0.05 |
| q_vel = 2.65 |
| self.Q = numpy.matrix( |
| numpy.diag([(q_pos**2.0), (q_vel**2.0), (q_pos**2.0), |
| (q_vel**2.0)])) |
| |
| r_nm = 0.025 |
| self.R = numpy.matrix(numpy.diag([(r_nm**2.0), (r_nm**2.0)])) |
| |
| self.KalmanGain, self.Q_steady = controls.kalman(A=self.A, |
| B=self.B, |
| C=self.C, |
| Q=self.Q, |
| R=self.R) |
| |
| # 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 DelayedIntake(Intake): |
| |
| def __init__(self, name="DelayedIntake"): |
| super(DelayedIntake, self).__init__(name=name) |
| |
| self.A_undelayed = self.A |
| self.B_undelayed = self.B |
| |
| self.C_unaugmented = self.C |
| self.C = numpy.matrix(numpy.zeros((2, 5))) |
| self.C[0:2, 0:4] = self.C_unaugmented |
| |
| # Model this as X[4] is the last power. And then B applies to the last |
| # power. This lets us model the 1 cycle PWM delay accurately. |
| self.A = numpy.matrix(numpy.zeros((5, 5))) |
| self.A[0:4, 0:4] = self.A_undelayed |
| self.A[0:4, 4] = self.B_undelayed |
| self.B = numpy.matrix(numpy.zeros((5, 1))) |
| self.B[4, 0] = 1.0 |
| |
| # Coordinate transform fom absolute angles to relative angles. |
| # [output_position, output_velocity, spring_angle, spring_velocity, voltage] |
| abs_to_rel = numpy.matrix([[1.0, 0.0, 0.0, 0.0, 0.0], |
| [0.0, 1.0, 0.0, 0.0, 0.0], |
| [1.0, 0.0, -1.0, 0.0, 0.0], |
| [0.0, 1.0, 0.0, -1.0, 0.0], |
| [0.0, 0.0, 0.0, 0.0, 1.0]]) |
| # and back again. |
| rel_to_abs = numpy.matrix(numpy.linalg.inv(abs_to_rel)) |
| |
| # Now, get A and B in the relative coordinate system. |
| self.A_transformed_full = numpy.matrix(numpy.zeros((5, 5))) |
| self.B_transformed_full = numpy.matrix(numpy.zeros((5, 1))) |
| (self.A_transformed_full[0:4, 0:4], |
| self.A_transformed_full[0:4, 4]) = self.ContinuousToDiscrete( |
| abs_to_rel[0:4, 0:4] * self.A_continuous * rel_to_abs[0:4, 0:4], |
| abs_to_rel[0:4, 0:4] * self.B_continuous, self.dt) |
| self.B_transformed_full[4, 0] = 1.0 |
| |
| # Pull out the components of the dynamics which don't include the spring |
| # output position so we can do partial state feedback on what we care about. |
| self.A_transformed = self.A_transformed_full[1:5, 1:5] |
| self.B_transformed = self.B_transformed_full[1:5, 0] |
| |
| glog.debug('A_transformed_full ' + str(self.A_transformed_full)) |
| glog.debug('B_transformed_full ' + str(self.B_transformed_full)) |
| glog.debug('A_transformed ' + str(self.A_transformed)) |
| glog.debug('B_transformed ' + str(self.B_transformed)) |
| |
| # Now, let's design a controller in |
| # [output_velocity, spring_position, spring_velocity, delayed_voltage] |
| # space. |
| |
| q_output_vel = 1.0 |
| q_spring_pos = 0.10 |
| q_spring_vel = 2.0 |
| q_voltage = 1000000000000.0 |
| self.Q_lqr = numpy.matrix( |
| numpy.diag([ |
| 1.0 / (q_output_vel**2.0), 1.0 / (q_spring_pos**2.0), |
| 1.0 / (q_spring_vel**2.0), 1.0 / (q_voltage**2.0) |
| ])) |
| |
| self.R = numpy.matrix([[(1.0 / (12.0**2.0))]]) |
| |
| self.K_transformed = controls.dlqr(self.A_transformed, |
| self.B_transformed, self.Q_lqr, |
| self.R) |
| |
| # Write the controller back out in the absolute coordinate system. |
| self.K = numpy.hstack( |
| (numpy.matrix([[0.0]]), self.K_transformed)) * abs_to_rel |
| |
| controllability = controls.ctrb(self.A_transformed, self.B_transformed) |
| glog.debug('ctrb: ' + repr(numpy.linalg.matrix_rank(controllability))) |
| |
| w, v = numpy.linalg.eig(self.A_transformed - |
| self.B_transformed * self.K_transformed) |
| glog.debug('Poles are %s, for %s', repr(w), self._name) |
| |
| for i in range(len(w)): |
| glog.debug(' Pole %s -> %s', repr(w[i]), v[:, i]) |
| |
| glog.debug('K is %s', repr(self.K_transformed)) |
| |
| # Design a kalman filter here as well. |
| q_pos = 0.05 |
| q_vel = 2.65 |
| q_volts = 0.005 |
| self.Q = numpy.matrix( |
| numpy.diag([(q_pos**2.0), (q_vel**2.0), (q_pos**2.0), (q_vel**2.0), |
| (q_volts**2.0)])) |
| |
| r_nm = 0.025 |
| self.R = numpy.matrix(numpy.diag([(r_nm**2.0), (r_nm**2.0)])) |
| |
| glog.debug('Overall poles are %s, for %s', |
| repr(numpy.linalg.eig(self.A - self.B * self.K)[0]), |
| self._name) |
| |
| self.KalmanGain, self.Q_steady = controls.kalman(A=self.A, |
| B=self.B, |
| C=self.C, |
| Q=self.Q, |
| R=self.R) |
| |
| self.InitializeState() |
| |
| |
| class ScenarioPlotter(object): |
| |
| def __init__(self): |
| # Various lists for graphing things. |
| self.t = [] |
| self.x_motor = [] |
| self.x_output = [] |
| self.v = [] |
| self.goal_v = [] |
| self.a = [] |
| self.spring = [] |
| self.x_hat = [] |
| self.u = [] |
| |
| def run_test(self, |
| intake, |
| iterations=400, |
| controller_intake=None, |
| observer_intake=None): |
| """Runs the intake plant with an initial condition and goal. |
| |
| Test for whether the goal has been reached and whether the separation |
| goes outside of the initial and goal values by more than |
| max_separation_error. |
| |
| Prints out something for a failure of either condition and returns |
| False if tests fail. |
| Args: |
| intake: intake object to use. |
| iterations: Number of timesteps to run the model for. |
| 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. |
| """ |
| |
| 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 |
| |
| # Delay U by 1 cycle in our simulation to make it more realistic. |
| last_U = numpy.matrix([[0.0]]) |
| intake.Y = intake.C * intake.X |
| |
| # Start with the intake deflected by 0.2 radians |
| # intake.X[0,0] = 0.2 |
| # intake.Y[0,0] = intake.X[0,0] |
| # observer_intake.X_hat[0,0] = intake.X[0,0] |
| |
| for i in range(iterations): |
| X_hat = intake.X |
| |
| if observer_intake is not None: |
| X_hat = observer_intake.X_hat |
| self.x_hat.append(observer_intake.X_hat[0, 0]) |
| |
| goal_angle = 3.0 |
| goal_velocity = numpy.clip((goal_angle - X_hat[0, 0]) * 6.0, -1.0, |
| 1.0) |
| |
| self.goal_v.append(goal_velocity) |
| |
| # Nominal: 1.8 N at 0.25 m -> 0.45 N m |
| # Nominal: 13 N at 0.25 m at 0.5 radians -> 3.25 N m -> 6 N m / radian |
| |
| R = numpy.matrix([[0.0], [goal_velocity], [0.0], [goal_velocity], |
| [goal_velocity / (intake.G * intake.Kv)]]) |
| U = controller_intake.K * (R - X_hat) + R[4, 0] |
| |
| U[0, 0] = numpy.clip(U[0, 0], -vbat, vbat) # * 0.0 |
| |
| self.x_output.append(intake.X[0, 0]) |
| self.x_motor.append(intake.X[2, 0]) |
| self.spring.append(intake.X[0, 0] - intake.X[2, 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) |
| |
| if observer_intake is not None: |
| observer_intake.Y = intake.Y |
| observer_intake.CorrectObserver(U) |
| |
| intake.Update(last_U + 0.0) |
| |
| if observer_intake is not None: |
| observer_intake.PredictObserver(U) |
| |
| self.t.append(initial_t + i * intake.dt) |
| self.u.append(U[0, 0]) |
| last_U = U |
| |
| def Plot(self): |
| pylab.subplot(3, 1, 1) |
| pylab.plot(self.t, self.x_output, label='x output') |
| pylab.plot(self.t, self.x_motor, label='x motor') |
| pylab.plot(self.t, self.x_hat, label='x_hat') |
| pylab.legend() |
| |
| spring_ax1 = pylab.subplot(3, 1, 2) |
| spring_ax1.plot(self.t, self.u, 'k', label='u') |
| spring_ax2 = spring_ax1.twinx() |
| spring_ax2.plot(self.t, self.spring, label='spring_angle') |
| spring_ax1.legend(loc=2) |
| spring_ax2.legend() |
| |
| accel_ax1 = pylab.subplot(3, 1, 3) |
| accel_ax1.plot(self.t, self.a, 'r', label='a') |
| |
| accel_ax2 = accel_ax1.twinx() |
| accel_ax2.plot(self.t, self.v, label='v') |
| accel_ax2.plot(self.t, self.goal_v, label='goal_v') |
| accel_ax1.legend(loc=2) |
| accel_ax2.legend() |
| |
| pylab.show() |
| |
| |
| def main(argv): |
| scenario_plotter = ScenarioPlotter() |
| |
| intake = Intake() |
| intake.X[0, 0] = 0.0 |
| intake_controller = DelayedIntake() |
| observer_intake = DelayedIntake() |
| observer_intake.X_hat[0, 0] = intake.X[0, 0] |
| |
| # Test moving the intake with constant separation. |
| scenario_plotter.run_test(intake, |
| controller_intake=intake_controller, |
| observer_intake=observer_intake, |
| iterations=200) |
| |
| 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 intake and delayed_intake.' |
| ) |
| else: |
| namespaces = ['y2018', 'control_loops', 'superstructure', 'intake'] |
| intake = Intake('Intake') |
| loop_writer = control_loop.ControlLoopWriter('Intake', [intake], |
| namespaces=namespaces) |
| loop_writer.AddConstant( |
| control_loop.Constant('kGearRatio', '%f', intake.G)) |
| loop_writer.AddConstant( |
| control_loop.Constant('kMotorVelocityConstant', '%f', intake.Kv)) |
| loop_writer.AddConstant( |
| control_loop.Constant('kFreeSpeed', '%f', intake.free_speed)) |
| loop_writer.Write(argv[1], argv[2]) |
| |
| delayed_intake = DelayedIntake('DelayedIntake') |
| loop_writer = control_loop.ControlLoopWriter('DelayedIntake', |
| [delayed_intake], |
| namespaces=namespaces) |
| loop_writer.Write(argv[3], argv[4]) |
| |
| |
| if __name__ == '__main__': |
| argv = FLAGS(sys.argv) |
| glog.init() |
| sys.exit(main(argv)) |