def __init__(self, n=50, max_iter=100, **kwargs):
'''
n int: length of the control sequence
max_iter int: limit on number of optimization iterations
'''
super(Control, self).__init__(**kwargs)
self.old_target = [None, None]
self.tN = n # number of timesteps
self.max_iter = max_iter
self.lamb_factor = 10
self.lamb_max = 1000
self.eps_converge = 0.001 # exit if relative improvement below threshold
if self.write_to_file is True:
from controllers.recorder import Recorder
# set up recorders
self.u_recorder = Recorder('control signal', self.task, 'ilqr')
self.xy_recorder = Recorder('end-effector position', self.task,
'ilqr')
self.dist_recorder = Recorder('distance from target', self.task,
'ilqr')
self.recorders = [
self.u_recorder, self.xy_recorder, self.dist_recorder
]
def __init__(self, **kwargs):
super(Control, self).__init__(**kwargs)
# generalized coordinates
self.target_gain = 2 * np.pi
self.target_bias = -np.pi
if self.write_to_file is True:
from controllers.recorder import Recorder
# set up recorders
self.u_recorder = Recorder('control signal', self.task, 'gc')
self.xy_recorder = Recorder('end-effector position', self.task,
'gc')
self.dist_recorder = Recorder('distance from target', self.task,
'gc')
self.recorders = [
self.u_recorder, self.xy_recorder, self.dist_recorder
]