Control

def control_operating_conditions(t, solver_variables, operating_inputs, parameters, control_variables):
    """This function controls the operating conditions of the MEA system, if required.
    This is an elementary rule-based control, serving as a demonstrator. It will need to be improved in the future.

    Parameters
    ----------
    t : float
        Time (s).
    solver_variables : dict
        Dictionary containing the solver variables.
    operating_inputs : dict
        Dictionary containing the operating inputs.
    parameters : dict
        Dictionary containing the parameters.
    control_variables : dict
        Dictionary containing the control variables.
    """

    if parameters["type_control"] != "Phi_des":
        raise ValueError('You have to specify a type_control which is accepted.')

    elif parameters["type_control"] == "Phi_des":
        # Initialisation
        delta_t_control_Phi = 20  # s. Every delta_t_control_Phi second the cell humidity is controlled.
        delta_Phi_des = 0.01  # Arbitrary value for the step change of Phi_des.
        slim = parameters['a_slim'] * (operating_inputs['Pc_des'] / 1e5) + parameters['b_slim']
        s_ccl_max = 0.55 * slim  # An arbitrary margin for s_ccl is established to ensure the CCL is not too flooded.
        #                          I may take s_switch instead of 0.55 ?
        lambda_mem_min = 8  # An arbitrary margin for lambda_mem is established to ensure the membrane is not too dry.

        # Control on Phi_des
        #       Every delta_t_control_Phi second, Phi_a_des is monitored for controlling the cell humidity.
        if t > (control_variables['t_control_Phi'] + delta_t_control_Phi):  # s.
            control_variables['t_control_Phi'] = control_variables['t_control_Phi'] + delta_t_control_Phi

            # Flooding is likely.
            if solver_variables['s_ccl'] > s_ccl_max and solver_variables['lambda_mem'] > lambda_mem_min:
                if control_variables['Phi_a_des'] - delta_Phi_des >= 0:
                    control_variables['Phi_a_des'] = control_variables['Phi_a_des'] - delta_Phi_des
                if control_variables['Phi_c_des'] - delta_Phi_des >= 0:
                    control_variables['Phi_c_des'] = control_variables['Phi_c_des'] - delta_Phi_des

            # Drying out is likely.
            elif solver_variables['lambda_mem'] < lambda_mem_min and solver_variables['s_ccl'] < s_ccl_max:
                if control_variables['Phi_a_des'] + delta_Phi_des <= 1:
                    control_variables['Phi_a_des'] = control_variables['Phi_a_des'] + delta_Phi_des
                if control_variables['Phi_c_des'] + delta_Phi_des <= 1:
                    control_variables['Phi_c_des'] = control_variables['Phi_c_des'] + delta_Phi_des

            # Both flooding and drying out are likely. Nothing can be done.
            elif solver_variables['s_ccl'] > s_ccl_max and solver_variables['lambda_mem'] < lambda_mem_min:
                pass

            # Both flooding and drying out are unlikely. It is the desired situation.
            else:  # elif solver_variables['s_ccl'] < s_ccl_max and solver_variables['lambda_mem'] > lambda_mem_min:
                pass