from numpy import pi
from cart_pole import CartPole
from plot_graphs import visualize_plots
from render_movie import visualize_movie
from learning_system import LearningCorrection
play_movie = True
ideal_cart_pole = CartPole(
dt=.001,
init_conds=[0, 0., pi, 0.], #x, dx, phi, dphi
end=10,
)
ideal_cart_pole.compute_lqr_gain()
ideal_data = ideal_cart_pole.integrate()
dist_cart_pole = CartPole(
dt=.001,
init_conds=[0, 0., pi, 0.], #x, dx, phi, dphi
end=10,
disturb=False,
)
dist_cart_pole.compute_lqr_gain()
dist_data = dist_cart_pole.integrate()
# ## Learn the system model
lc = LearningCorrection(ideal_system=ideal_cart_pole,
ideal_data=ideal_data,
real_system=dist_cart_pole)
