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training_ml_control.control

training_ml_control.control#

Module Contents#

Classes#

FeedbackController

Observer

ConstantController

SineController

SumOfSineController

SchroederSweepController

PRBSController

RandomController

Functions#

build_lqr_controller

build_mpc_controller

Data#

__all__

API#

training_ml_control.control.__all__#

[‘FeedbackController’, ‘Observer’, ‘ConstantController’, ‘SineController’, ‘SumOfSineController’, ‘S…

class training_ml_control.control.FeedbackController[source]#

Bases: typing.Protocol

control(measurement: numpy.typing.NDArray) → numpy.typing.NDArray[source]#
class training_ml_control.control.Observer[source]#

Bases: typing.Protocol

observe(measurement: numpy.typing.NDArray) → numpy.typing.NDArray[source]#
class training_ml_control.control.ConstantController(u: numpy.typing.NDArray = np.zeros(1))[source]#

Initialization

act(measurement: numpy.typing.NDArray) → numpy.typing.NDArray[source]#
class training_ml_control.control.SineController(env: gymnasium.Env, u_max: numpy.typing.NDArray = np.asarray([10]), frequency: float = 1)[source]#

Initialization

act(measurement: numpy.typing.NDArray) → numpy.typing.NDArray[source]#
class training_ml_control.control.SumOfSineController(env: gymnasium.Env, u_max: numpy.typing.NDArray = np.asarray([10]), frequencies: list[float] = [1.0])[source]#

Initialization

act(measurement: numpy.typing.NDArray) → numpy.typing.NDArray[source]#
class training_ml_control.control.SchroederSweepController(env: gymnasium.Env, n_time_steps: int = 200, input_power: float = 10, n_harmonics: int = 3, frequency: float = 1)[source]#

Initialization

act(measurement: numpy.typing.NDArray) → numpy.typing.NDArray[source]#
class training_ml_control.control.PRBSController(u_max: numpy.typing.NDArray = np.asarray([10]), seed: int = 16)[source]#

Initialization

act(measurement: numpy.typing.NDArray) → numpy.typing.NDArray[source]#
class training_ml_control.control.RandomController(env: gymnasium.Env)[source]#

Initialization

act(measurement: numpy.typing.NDArray) → numpy.typing.NDArray[source]#
training_ml_control.control.build_lqr_controller(model: do_mpc.model.LinearModel, t_step: float, n_horizon: int | None, setpoint: numpy.typing.NDArray, Q: numpy.typing.NDArray, R: numpy.typing.NDArray) → do_mpc.controller.LQR[source]#
training_ml_control.control.build_mpc_controller(model: do_mpc.model.Model, t_step: float, n_horizon: int | None, terminal_cost, stage_cost, x_limits: dict[str, numpy.typing.NDArray] | None = None, u_limits: dict[str, numpy.typing.NDArray] | None = None, u_penalty: dict[str, float] | None = None, *, uncertainty_values: dict[str, numpy.typing.NDArray] | None = None, n_robust: int = 1) → do_mpc.controller.MPC[source]#
Contents