Made shooter python file velocity-only.
Still need to fix a couple of thins in the C++ files.
diff --git a/frc971/control_loops/python/shooter.py b/frc971/control_loops/python/shooter.py
index 83beb90..27ecc16 100755
--- a/frc971/control_loops/python/shooter.py
+++ b/frc971/control_loops/python/shooter.py
@@ -4,51 +4,57 @@
import sys
from matplotlib import pylab
import control_loop
+import slycot
class Shooter(control_loop.ControlLoop):
def __init__(self):
super(Shooter, self).__init__("Shooter")
# Stall Torque in N m
- self.stall_torque = 0.49819248
+ self.stall_torque = 2.42211227883219
# Stall Current in Amps
- self.stall_current = 85
+ self.stall_current = 133
# Free Speed in RPM
- self.free_speed = 19300.0 - 1500.0
+ self.free_speed = 4650.0
# Free Current in Amps
- self.free_current = 1.4
+ self.free_current = 2.7
# Moment of inertia of the shooter wheel in kg m^2
self.J = 0.0032
# Resistance of the motor, divided by 2 to account for the 2 motors
- self.R = 12.0 / self.stall_current / 2
+ self.R = 12.0 / self.stall_current
# 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 ratio
- self.G = 11.0 / 34.0
+ self.G = 40.0 / 34.0
# Control loop time step
self.dt = 0.01
# State feedback matrices
self.A_continuous = numpy.matrix(
- [[0, 1],
- [0, -self.Kt / self.Kv / (self.J * self.G * self.G * self.R)]])
+ [[-self.Kt / self.Kv / (self.J * self.G * self.G * self.R)]])
self.B_continuous = numpy.matrix(
- [[0],
- [self.Kt / (self.J * self.G * self.R)]])
- self.C = numpy.matrix([[1, 0]])
+ [[self.Kt / (self.J * self.G * self.R)]])
+ self.C = numpy.matrix([[1]])
self.D = numpy.matrix([[0]])
- self.ContinuousToDiscrete(self.A_continuous, self.B_continuous,
- self.dt, self.C)
+ self.A, self.B = self.ContinuousToDiscrete(self.A_continuous, self.B_continuous,
+ self.dt)
- self.PlaceControllerPoles([.6, .981])
+ self.InitializeState()
- self.rpl = .45
- self.ipl = 0.07
- self.PlaceObserverPoles([self.rpl + 1j * self.ipl,
- self.rpl - 1j * self.ipl])
+ self.PlaceControllerPoles([.8])
+ # LQR stuff for optimization, if needed.
+ #print self.K
+ #self.R_LQR = numpy.matrix([[1.5]])
+ #self.P = slycot.sb02od(1, 1, self.A, self.B, self.C * self.C.T, self.R, 'D')[0]
+ #self.K = (numpy.linalg.inv(self.R_LQR + self.B.T * self.P * self.B)
+ # * self.B.T * self.P * self.A)
+ #print numpy.linalg.eig(self.A - self.B * self.K)
+
+
+ self.PlaceObserverPoles([0.45])
self.U_max = numpy.matrix([[12.0]])
self.U_min = numpy.matrix([[-12.0]])
@@ -72,56 +78,47 @@
last_x = shooter_data[i, 2]
sim_delay = 1
- pylab.plot(range(sim_delay, shooter_data.shape[0] + sim_delay),
- simulated_x, label='Simulation')
- pylab.plot(range(shooter_data.shape[0]), real_x, label='Reality')
- pylab.plot(range(shooter_data.shape[0]), x_vel, label='Velocity')
- pylab.legend()
- pylab.show()
+# pylab.plot(range(sim_delay, shooter_data.shape[0] + sim_delay),
+# simulated_x, label='Simulation')
+# pylab.plot(range(shooter_data.shape[0]), real_x, label='Reality')
+# pylab.plot(range(shooter_data.shape[0]), x_vel, label='Velocity')
+# pylab.legend()
+# pylab.show()
# Simulate the closed loop response of the system to a step input.
shooter = Shooter()
close_loop_x = []
close_loop_U = []
- velocity_goal = 300
- R = numpy.matrix([[0.0], [velocity_goal]])
- for _ in pylab.linspace(0,1.99,200):
+ velocity_goal = 400
+ R = numpy.matrix([[velocity_goal]])
+ goal = False
+ for i in pylab.linspace(0,1.99,200):
# Iterate the position up.
- R = numpy.matrix([[R[0, 0] + 10.5], [velocity_goal]])
- # Prevents the position goal from going beyond what is necessary.
- velocity_weight_scalar = 0.35
- max_reference = (
- (shooter.U_max[0, 0] - velocity_weight_scalar *
- (velocity_goal - shooter.X_hat[1, 0]) * shooter.K[0, 1]) /
- shooter.K[0, 0] +
- shooter.X_hat[0, 0])
- min_reference = (
- (shooter.U_min[0, 0] - velocity_weight_scalar *
- (velocity_goal - shooter.X_hat[1, 0]) * shooter.K[0, 1]) /
- shooter.K[0, 0] +
- shooter.X_hat[0, 0])
- R[0, 0] = numpy.clip(R[0, 0], min_reference, max_reference)
- U = numpy.clip(shooter.K * (R - shooter.X_hat),
+ R = numpy.matrix([[velocity_goal]])
+ U = numpy.clip(shooter.K * (R - shooter.X_hat) +
+ (numpy.identity(shooter.A.shape[0]) - shooter.A) * R / shooter.B,
shooter.U_min, shooter.U_max)
shooter.UpdateObserver(U)
shooter.Update(U)
- close_loop_x.append(shooter.X[1, 0])
+ close_loop_x.append(shooter.X[0, 0])
close_loop_U.append(U[0, 0])
+ if (abs(R[0, 0] - shooter.X[0, 0]) < R[0, 0]* 0.01 and (not goal)):
+ goal = True
+ print i
#pylab.plotfile("shooter.csv", (0,1))
- #pylab.plot(pylab.linspace(0,1.99,200), close_loop_U, 'ro')
+ pylab.plot(pylab.linspace(0,1.99,200), close_loop_U)
#pylab.plotfile("shooter.csv", (0,2))
- pylab.plot(pylab.linspace(0,1.99,200), close_loop_x, 'ro')
+ pylab.plot(pylab.linspace(0,1.99,200), close_loop_x)
pylab.show()
# Simulate spin down.
spin_down_x = [];
- R = numpy.matrix([[50.0], [0.0]])
for _ in xrange(150):
U = 0
shooter.UpdateObserver(U)
shooter.Update(U)
- spin_down_x.append(shooter.X[1, 0])
+ spin_down_x.append(shooter.X[0, 0])
#pylab.plot(range(150), spin_down_x)
#pylab.show()