'actuator_force_period': 10, # * s
'activation_amplification': 1,
'activation_delay': 0.0, # * a delay for when to start activation
'constant_normalized_damping': 0.75, # * s : D/K : [N/m/s]/[N/m]
'linear_normalized_damping_coefficient': 3.5, # * A: s/m : D/F : [N/m/s]/N : 0.0035 N/mm/s -> 3.5 1/m/s from Kirch et al. Fig 12
'linear_minimum_normalized_damping': 0.05, # * 1/A*(kg*N/kg) :
'swing_leg_norm_angular_velocity': 0, # [1/s]/[m/s] (omega/(vx/lr))
'swing_velocity': 0, # rad/s (set by calculation)
'angle_of_attack_offset': 0} # rad (set by calculation)
# * linear_normalized_damping_coefficient:
# * A: s/m : D/F : [N/m/s]/N : 0.0035 N/mm/s -> 3.5 1/m/s (Kirch et al. Fig 12)
x0 = np.array([0, 1.00, 5.5, 0, 0, 0, p['actuator_resting_length'], 0, 0, 0])
x0 = model.reset_leg(x0, p)
p['total_energy'] = model.compute_total_energy(x0, p)
x0, p = model.create_open_loop_trajectories(x0, p)
p['x0'] = x0
p['activation_amplification'] = 1.5
# initialize default x0_daslip
p_map = model.poincare_map
p_map.p = p
p_map.x = x0
p_map.sa2xp = model.sa2xp_y_xdot_timedaoa
# p_map.sa2xp = model.sa2xp_y_xdot_aoa
p_map.xp2s = model.xp2s_y_xdot
s_grid_height = np.linspace(0.5, 1.5, 7)
s_grid_velocity = np.linspace(3, 8, 7)
s_grid = (s_grid_height, s_grid_velocity)
a_grid_aoa = np.linspace(00/180*np.pi, 70/180*np.pi, 21)
tictoc.tic()
name = 'guineafowl' # name folder and files to save data
# * find spring stiffness that results in limit cycle motion
legStiffnessSearchWidth = p['stiffness'] * 0.5
limit_cycle_options = {
'search_initial_state': False,
'state_index': 2, # not used
'state_search_width': 2.0, # not used
'search_parameter': True,
'parameter_name': 'stiffness',
'parameter_search_width': legStiffnessSearchWidth
}
print(p['stiffness'], ' N/m :Leg stiffness prior to fitting')
x0, p = model.create_open_loop_trajectories(x0, p, limit_cycle_options)
print(p['stiffness'], ' N/m :Leg stiffness after fitting')
# * Save parameter fit
if not os.path.exists(name):
os.makedirs(name)
filename = name + '/' + name + '_parameter_fit'
data2save = {
"p": p,
"x0": x0,
"limit_cycle_options": limit_cycle_options,
"damping_vals": damping_vals
}
outfile = open(filename + '.pickle', 'wb')
pickle.dump(data2save, outfile)