def plant(T, initD):
gain = sm.Gain(T)
delay_x = sm.R(0)
delay_y = sm.FeedbackAdd(sm.Gain(1), sm.R(initD))
return sm.Cascade(sm.Cascade(gain, delay_x), delay_y)
def plant(t, initD):
"""
Returns a state machine whose input is the commanded velocity
and whose output is the distance to the wall.
Args:
t - the duration of a time step
initD - the starting distance from the wall
"""
movement = sm.Gain(t)
position = sm.R(initD)
return sm.FeedbackAdd(movement, position)
def plant(T, initD):
return sm.Cascade(sm.Gain(-T), sm.FeedbackAdd(sm.R(initD), sm.Wire()))
def sensor(initD):
return sm.R(initD)
def accumulator(init):
none_there = sm.Gain(1)
y_delay = sm.R(init)
y = sm.FeedbackAdd(none_there, y_delay)
return y
def accumulatorDelay(init):
x_delay = sm.R(0)
return sm.Cascade(x_delay, accumulator(init))
def accumulatorDelay(init):
return sm.FeedbackAdd(sm.R(init), sm.Gain(1.0))
def accumulatorDelayScaled(init, s):
return sm.Cascade(sm.FeedbackAdd(sm.R(init), sm.Gain(1.0)), sm.Gain(s))
def accumulator(init):
"""
Returns a state machine such that y[n] = y[n-1] + x[n] with a starting state of init.
"""
return sm.FeedbackAdd(sm.Gain(1), sm.R(init))
def accumulatorDelay(init):
"""
Returns a state machine such that y[n] = y[n-1] + x[n-1] witgh a starting state of init.
"""
return sm.Cascade(accumulator(init), sm.R(init))
def sensor(initD):
"""
Returns a state machine whose input should be the distance to the wall
and whose output should be the delayed distance to the wall.
"""
return sm.R(initD)
