Private API

abstract type AbstractDiscretizer <: CTSolvers.Strategies.AbstractStrategy

Abstract type for optimal control problem discretization strategies.

This type defines the interface for converting continuous optimal control problems into discrete optimization problems suitable for numerical solvers. Subtypes must implement the callable interface to perform the actual discretization.

Interface Requirements

Subtypes must implement:

• (discretizer::AbstractDiscretizer)(ocp::AbstractModel): Perform discretization

Example

julia> using CTDirect

julia> MyDiscretizer <: AbstractDiscretizer end

julia> # Implement the required interface
julia> (d::MyDiscretizer)(ocp) = discretize_collocation(ocp)

See also: Collocation, discretize

abstract type Discretization

Abstract type representing a discretization strategy for an optimal control problem.

Concrete subtypes of Discretization define specific schemes for transforming a continuous-time problem into a discrete-time representation suitable for numerical solution.

Example

julia> struct MyDiscretization <: Discretization end
MyDiscretization

__discretizer() -> CTDirect.Collocation

Returns the default discretizer instance used by the convenience method.

This function provides the default collocation discretizer that is used when no specific discretizer is provided to the discretize function.

Returns

• AbstractDiscretizer: The default collocation discretizer instance

Notes

• This function is internal and primarily used for providing default values
• The default is currently Collocation() but may change in future versions

See also: discretize, Collocation

discretize(
    ocp::CTModels.OCP.AbstractModel,
    discretizer::CTDirect.AbstractDiscretizer
) -> CTSolvers.DOCP.DiscretizedModel{TO, TAMB, TEMB, TASB, TESB} where {TO<:CTModels.OCP.AbstractModel, TAMB<:(CTSolvers.Optimization.ADNLPModelBuilder{T} where T<:(CTDirect.var"#build_adnlp_model#build_adnlp_model##0"{CTDirect.var"#build_adnlp_model#5#9"{docp}} where docp)), TEMB<:(CTSolvers.Optimization.ExaModelBuilder{T} where T<:(CTDirect.var"#build_exa_model#build_exa_model##0"{CTDirect.var"#build_exa_model#8#14"{CTDirect.Collocation, var"#s179", T}} where {var"#s179"<:CTModels.OCP.AbstractModel, T})), TASB<:(CTSolvers.Optimization.ADNLPSolutionBuilder{T} where T<:CTDirect.var"#build_adnlp_solution#build_adnlp_solution##0"), TESB<:(CTSolvers.Optimization.ExaSolutionBuilder{T} where T<:CTDirect.var"#build_exa_solution#build_exa_solution##0")}

Discretize an optimal control problem using the specified discretizer.

This function applies a discretization strategy to convert a continuous optimal control problem into a form suitable for numerical optimization.

Arguments

• ocp::AbstractModel: The optimal control problem to discretize
• discretizer::AbstractDiscretizer: The discretization strategy to apply

Returns

• The discretized problem (type depends on the specific discretizer)

Example

julia> using CTDirect

julia> ocp = create_ocp()  # Create your OCP
julia> discretized = discretize(ocp, Collocation())

See also: AbstractDiscretizer, Collocation

discretize(
    ocp::CTModels.OCP.AbstractModel;
    discretizer
) -> CTSolvers.DOCP.DiscretizedModel{TO, TAMB, TEMB, TASB, TESB} where {TO<:CTModels.OCP.AbstractModel, TAMB<:(CTSolvers.Optimization.ADNLPModelBuilder{T} where T<:(CTDirect.var"#build_adnlp_model#build_adnlp_model##0"{CTDirect.var"#build_adnlp_model#5#9"{docp}} where docp)), TEMB<:(CTSolvers.Optimization.ExaModelBuilder{T} where T<:(CTDirect.var"#build_exa_model#build_exa_model##0"{CTDirect.var"#build_exa_model#8#14"{CTDirect.Collocation, var"#s179", T}} where {var"#s179"<:CTModels.OCP.AbstractModel, T})), TASB<:(CTSolvers.Optimization.ADNLPSolutionBuilder{T} where T<:CTDirect.var"#build_adnlp_solution#build_adnlp_solution##0"), TESB<:(CTSolvers.Optimization.ExaSolutionBuilder{T} where T<:CTDirect.var"#build_exa_solution#build_exa_solution##0")}

Discretize an optimal control problem using the default discretizer.

This is a convenience method that uses the default collocation discretizer when no specific discretizer is provided.

Arguments

• ocp::AbstractModel: The optimal control problem to discretize
• discretizer::AbstractDiscretizer: The discretization strategy (default: Collocation())

Returns

• The discretized problem using the specified or default discretizer

Example

julia> using CTDirect

julia> ocp = create_ocp()  # Create your OCP
julia> discretized = discretize(ocp)  # Uses default Collocation
julia> discretized_custom = discretize(ocp, MyCustomDiscretizer())

Notes

• The default discretizer is Collocation()
• For custom discretization, provide a specific discretizer instance

See also: AbstractDiscretizer, Collocation