def main():
'main function'
ctrlLimits = CtrlLimits()
flightLimits = FlightLimits()
llc = LowLevelController(ctrlLimits)
setpoint = 2220
p_gain = 0.01
ap = FixedSpeedAutopilot(setpoint, p_gain, llc.xequil, llc.uequil,
flightLimits, ctrlLimits)
pass_fail = AirspeedPFA(60, setpoint, 5)
### Initial Conditions ###
power = 0 # Power
# Default alpha & beta
alpha = deg2rad(2.1215) # Trim Angle of Attack (rad)
beta = 0 # Side slip angle (rad)
alt = 20000 # Initial Attitude
Vt = 1000 # Initial Speed
phi = 0 #(pi/2)*0.5 # Roll angle from wings level (rad)
theta = 0 #(-pi/2)*0.8 # Pitch angle from nose level (rad)
psi = 0 #-pi/4 # Yaw angle from North (rad)
# Build Initial Condition Vectors
# state = [VT, alpha, beta, phi, theta, psi, P, Q, R, pn, pe, h, pow]
initialState = [
Vt, alpha, beta, phi, theta, psi, 0, 0, 0, 0, 0, alt, power
]
# Select Desired F-16 Plant
f16_plant = 'morelli' # 'stevens' or 'morelli'
tMax = 70 # simulation time
def der_func(t, y):
'derivative function'
der = controlledF16(t, y, f16_plant, ap, llc)[0]
rv = np.zeros((y.shape[0], ))
rv[0] = der[0] # speed
rv[12] = der[12] # power lag term
return rv
passed, times, states, modes, ps_list, Nz_list, u_list = \
RunF16Sim(initialState, tMax, der_func, f16_plant, ap, llc, pass_fail, sim_step=0.1)
print "Simulation Conditions Passed: {}".format(passed)
# plot
filename = None # engine_e.png
plot2d(filename, times, [(states, [(0, 'Vt'), (12, 'Pow')]),
(u_list, [(0, 'Throttle')])])
def simulate(self):
clock = 0
self.file = open(self.data, "w")
X, Y = update_data(self.N, self.file, clock, self, [], [])
for i in range(self.iterations):
self.next_iter()
print(i, len(self.marked))
clock += self.dtime
X, Y = update_data(self.N, self.file, clock, self, X, Y)
plot2d(X, Y)
self.file.close()
with open("data/" + DATASET + ".csv", 'rb') as rawcsv:
# np.set_printoptions(threshold=np.inf, suppress=True)
data_orig = csv.reader(rawcsv, delimiter=',')
data, dates, wind = utils.format_data(data_orig)
date_vector = dates[:, 0]
date_vector *= 12.0
date_vector += 1
print(data.shape)
print(date_vector.shape)
plot.plot2d((date_vector, data[:, 1]),
DATASET + "-temp-time",
c="black",
a=0.2)
plot.plot2d((date_vector, data[:, 7]),
DATASET + "-humidity-time",
c="black",
a=0.2)
plot.plot2d((date_vector, wind),
DATASET + "-winddir-time",
c="black",
a=0.2)
plot.plot2d((date_vector, wind),
DATASET + "-winddir-speed",
c=data[:, 16],
a=0.2)
plot.plot2d((date_vector, wind),
DATASET + "-winddir-moisture-time",
from sklearn import manifold, decomposition, cluster
import plot
import utils
# Only looks at MDW cuz this is slow,
# and MDW offers enough interesting things to see (or lack thereof)
with open('data/MDW.csv', 'rb') as MDWcsv:
# np.set_printoptions(threshold=np.inf, suppress=True)
csv = csv.reader(MDWcsv, delimiter=',')
data = utils.format_data(csv)[0]
print("Using PCA, n=2")
pca = decomposition.PCA(n_components=2)
output = pca.fit_transform(data)
plot.plot2d(tuple(output[::7].T), "humidity-pca", c=data[::7, 7], a=0.8)
plot.plot2d(tuple(output[::7].T), "temperature-pca", c=data[::7, 1], a=0.8)
print("Using PCA, n=3")
pca = decomposition.PCA(n_components=3)
output = pca.fit_transform(data)
plot.plot3d_anim(tuple(output[::7].T),
"humidity-pca3d",
c=data[::7, 7],
a=0.8)
plot.plot3d_anim(tuple(output[::7].T),
"temperature-pca3d",
c=data[::7, 1],
a=0.8)
print("Using tSNE, n=2, p=100, training on [::7]")
(griewank, 0, (-100, 100), (0, 0))]
table_data = []
for objective_function in objective_function_list:
for topology in topology_list:
for pso_variant in pso_variant_list:
for influence_model in influence_model_list:
solution, objective_function_value, error_value = pso.run(topology,
pso_variant,
influence_model,
objective_function)
table_data += [[objective_function[0].__name__,
pso_variant,
topology,
str(influence_model),
str(solution),
objective_function_value,
error_value]]
print_table_data(table_data)
if __name__ == "__main__":
# main()
plot2d(rosenbrock, [-0.7, 0.8])
plot2d(sphere, [-5, 5])
plot2d(rastrigin, [-5, 5])
plot2d(griewank, [-10, 10])
def main():
'main function'
ctrlLimits = CtrlLimits()
flightLimits = FlightLimits()
llc = LowLevelController(ctrlLimits)
setpoint = 550 # altitude setpoint
ap = FixedAltitudeAutopilot(setpoint, llc.xequil, llc.uequil, flightLimits, ctrlLimits)
pass_fail = FlightLimitsPFA(flightLimits)
pass_fail.break_on_error = False
### Initial Conditions ###
power = 0 # Power
# Default alpha & beta
alpha = 0 # angle of attack (rad)
beta = 0 # Side slip angle (rad)
alt = 500 # Initial Attitude
Vt = 540 # Initial Speed
phi = 0
theta = alpha
psi = 0
# Build Initial Condition Vectors
# state = [VT, alpha, beta, phi, theta, psi, P, Q, R, pn, pe, h, pow]
initialState = [Vt, alpha, beta, phi, theta, psi, 0, 0, 0, 0, 0, alt, power]
# Select Desired F-16 Plant
f16_plant = 'morelli' # 'stevens' or 'morelli'
tMax = 15.0 # simulation time
def der_func(t, y):
'derivative function for RK45'
der = controlledF16(t, y, f16_plant, ap, llc)[0]
rv = np.zeros((y.shape[0],))
rv[0] = der[0] # air speed
rv[1] = der[1] # alpha
rv[4] = der[4] # pitch angle
rv[7] = der[7] # pitch rate
rv[11] = der[11] # altitude
rv[12] = der[12] # power lag term
rv[13] = der[13] # Nz integrator
return rv
passed, times, states, modes, ps_list, Nz_list, u_list = \
RunF16Sim(initialState, tMax, der_func, f16_plant, ap, llc, pass_fail, sim_step=0.01)
print("Simulation Conditions Passed: {}".format(passed))
# plot
filename = None # longitudinal.png
plot2d(filename, times, [
(states, [(0, 'Vt'), (11, 'Altitude')]), \
(u_list, [(0, 'Throttle'), (1, 'elevator')]), \
(Nz_list, [(0, 'Nz')]) \
])
