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ControllerCouplingParametersBasis - Source Code

File: Distributed_Design_Optimizer/subsystem/couplingparameters/ControllerCouplingParametersBasis.py

# Copyright (C) The DistributedDesignOptimizer Contributors
# Licensed under the GNU General Public License v3.0. See LICENSE file for details.
"""Controller coupling parameters basis module.

This module provides the base class for controller-level coupling
parameters in hierarchical distributed optimization.
"""

from Distributed_Design_Optimizer.subsystem.couplingparameters import CouplingParametersBasis


class ControllerCouplingParametersBasis(CouplingParametersBasis):
    """Base class for controller-level coupling parameters in hierarchical coordination.

    Holds the coupling parameters between a controller subsystem and a single
    local subsystem. The controller exchanges auxiliary variables (controller
    to local) and local coupling information (local to controller). Subclasses
    add algorithm-specific attributes (e.g., ALADIN auxiliary variables and
    Jacobians).

    The storage is defined as follows::

                          subsystem 0
                      //                 \\

        localcoupling 0 -> C         auxiliary C -> 0
        information

                      \\                  //
                          Controller
    """

    def __init__(self, id: str) -> None:
        """Initialize controller coupling parameters.

        Args:
            id: Identifier of the neighboring subsystem.
        """
        super().__init__(id)

        # Update coupling information for controller in separate class inheriting from this class for every algorithm, 
        # e.g. auxilairy variables 
        # (from CouplingsParametersBasis.py, it is inherited as designvariables) and jacobian,...

    def update_state(self, other_coupling: 'ControllerCouplingParametersBasis') -> None:
        """Update the state of this ControllerCouplingParametersBasis with values from another instance.

        This method is necessary for multiprocessing. When subsystems are executed in parallel
        using multiprocessing.Pool, they are serialized and deserialized, creating new objects
        in separate memory spaces. After parallel execution completes, this method updates
        the original object's attribute values while preserving their memory addresses.

        Note: This base class does not define any local attributes. Subclasses that add
        algorithm-specific attributes (e.g., auxiliary variables, jacobians) must override
        this method to update those attributes while calling super().update_state().

        Args:
            other_coupling: The source ControllerCouplingParametersBasis containing updated values
                from parallel execution.
        """
        # Call the base class update_state to handle inherited attributes (_id from CouplingParametersBasis)
        super().update_state(other_coupling=other_coupling)