# initializer for a specific speed
load_init = {'states': {'omega': 20}}
if __name__ == '__main__':
env = gem.make(
'DcSeriesCont-v1',
visualization=MotorDashboard(plots=['omega', 'i'], dark_mode=False),
motor_parameter=dict(j_rotor=0.001),
load_parameter=dict(a=0, b=0.1, c=0, j_load=0.001),
ode_solver='scipy.solve_ivp',
solver_kwargs=dict(),
reference_generator=rg.SwitchedReferenceGenerator(
sub_generators=[
rg.SinusoidalReferenceGenerator(reference_state='omega'),
rg.WienerProcessReferenceGenerator(reference_state='omega'),
rg.StepReferenceGenerator(reference_state='omega')
],
p=[0.2, 0.6, 0.2],
super_episode_length=(1000, 10000)),
# Pass the predefined initializers
motor_initializer=gaussian_init,
load_initializer=uniform_init,
)
# After the setup is done, we are ready to simulate the environment
# We make use of a standard PI speed controller
controller = Controller.make('pi_controller', env)
start = time.time()
cum_rew = 0
'''
# We will have a look at a current control scenario here
const_sub_gen = [
# operation at 10 % of the current limit
rg.ConstReferenceGenerator(reference_state='i', reference_value=0.1),
# operation at 90 % of the current limit
rg.ConstReferenceGenerator(reference_state='i', reference_value=0.9),
# operation at 110 % of the current limit,
rg.ConstReferenceGenerator(reference_state='i', reference_value=1.1)
]
# since the case of 110 % current may lead to limit violation, we only assign a small probability of 2 % to it
const_switch_gen = rg.SwitchedReferenceGenerator(
const_sub_gen, p=[0.49, 0.49, 0.02], super_episode_length=(1000, 2000)
)
# The ExternalSpeedLoad class allows to pass an arbitrary function of time which will then dictate the speed profile.
# As shown here it can also contain more parameters. Some examples:
# Parameterizable sine oscillation
sinus_lambda = (lambda t, frequency, amplitude, bias: amplitude * np.sin(2 * np.pi * frequency * t) + bias)
# Constant speed
constant_lambda = (lambda t, value: value)
# Parameterizable triangle oscillation
triangle_lambda = (lambda t, amplitude, frequency, bias: amplitude * signal.sawtooth(2 * np.pi * frequency * t,
width=0.5) + bias)
# Parameterizable sawtooth oscillation
saw_lambda = (lambda t, amplitude, frequency, bias: amplitude * signal.sawtooth(2 * np.pi * frequency * t,
width=0.9) + bias)
env = gem.make(
'emotor-dc-series-cont-v1',
# Pass an instance
visualization=MotorDashboard(plotted_variables='all', visu_period=1),
motor_parameter=dict(r_a=15e-3, r_e=15e-3, l_a=1e-3, l_e=1e-3),
# Take standard class and pass parameters (Load)
load_parameter=dict(a=0.01, b=.1, c=0.1, j_load=.06),
# Pass a string (with extra parameters)
ode_solver='euler',
solver_kwargs={},
# Pass a Class with extra parameters
reference_generator=rg.SwitchedReferenceGenerator(
sub_generators=[
rg.SinusoidalReferenceGenerator,
rg.WienerProcessReferenceGenerator(),
rg.StepReferenceGenerator()
],
p=[0.1, 0.8, 0.1],
super_episode_length=(1000, 10000)))
controller = Controller.make('cascaded_pi', env)
state, reference = env.reset()
start = time.time()
cum_rew = 0
for i in range(100000):
env.render()
action = controller.control(state, reference)
(state, reference), reward, done, _ = env.step(action)
cum_rew += reward
print(cum_rew)
#'DcExtExCont-v1', visualization=MotorDashboard(plots=['omega', 'torque', 'i_a', 'i_e', 'u_a', 'u_e'], visu_period=1), motor_parameter=dict(j_rotor=0.00005), load_parameter={'a': 0, 'b': 0, 'c': 0, 'j_load': 0},
'DcPermExCont-v1',
visualization=MotorDashboard(plots=['omega', 'torque', 'i', 'u'],
visu_period=1),
#'DcSeriesCont-v1', visualization=MotorDashboard(plots=['omega', 'torque', 'i', 'u'], visu_period=1),
#'DcShuntCont-v1', visualization=MotorDashboard(plots=['omega', 'torque', 'i_a', 'i_e', 'u'], visu_period=1),
ode_solver='scipy.solve_ivp',
solver_kwargs=dict(),
#load=ConstantSpeedLoad(omega_fixed=50 * np.pi / 30),
reference_generator=rg.SwitchedReferenceGenerator(
sub_generators=[
rg.SinusoidalReferenceGenerator(reference_state=ref,
amplitude_range=(0, 0.3),
offset_range=(0, 0.2)),
rg.WienerProcessReferenceGenerator(reference_state=ref,
amplitude_range=(0, 0.3),
offset_range=(0, 0.2)),
rg.StepReferenceGenerator(reference_state=ref,
amplitude_range=(0, 0.3),
offset_range=(0, 0.2))
],
p=[0.5, 0.25, 0.25],
super_episode_length=(10000, 100000)),
)
try:
controller = Controller.make('pid_controller',
env,
param_dict={
'p_gain': 10,
'i_gain': 15
})