DOCP

Struct for discretized optimal control problem DOCP

Contains:

• a copy of the original OCP
• the discretized DOCP as a NLP problem
• data required to link the OCP with the discretized DOCP

Internal struct for DOCP boolean flags

• freet0: OCP has free initial time
• freetf: OCP has free final time
• lagrange: OCP has a lagrange cost
• mayer: OCP has a mayer cost
• lagrangetomayer: convert lagrange cost to mayer form
• max: OCP is a maximization problem

Internal struct for DOCP bounds

• var_l: lower bounds for the NLP variables
• var_u: upper bounds for the NLP variables
• con_l: lower bounds for the NLP constraints
• con_u: upper bounds for the NLP constraints

Internal struct for DOCP dimensions

• NLP_x: state dimension including additional component for reformulated lagrange cost
• NLP_u: control dimension
• NLP_v: variable dimension
• OCP_x: state dimension for the original OCP
• path_cons: path constraints dimension
• boundary_cons: boundary constraints dimension

Internal struct for DOCP time grid

• steps: number of time steps
• normalized_grid: time grid rescaled to [0,1]
• fixed_grid: fixed time grid [t0,tf]

DOCP_constraints!(c, xu, docp::CTDirect.DOCP) -> Any

Compute the constraints C for the DOCP problem (modeled as LB <= C(X) <= UB).

DOCP_initial_guess(docp::CTDirect.DOCP) -> Vector{Float64}
DOCP_initial_guess(
    docp::CTDirect.DOCP,
    init::CTModels.Init
) -> Vector{Float64}

Build initial guess for discretized problem

DOCP_objective(xu, docp::CTDirect.DOCP) -> Any

Compute the objective for the DOCP problem.

build_bounds(
    dim_var,
    dim_box,
    box_triplet
) -> Tuple{Any, Any}

Build full, ordered sets of bounds for state, control or optimization variables

constraints_bounds!(
    docp::CTDirect.DOCP
) -> Tuple{Vector{Float64}, Vector{Float64}}

Build upper and lower bounds vectors for the DOCP nonlinear constraints.

get_time_grid(xu, docp::CTDirect.DOCP) -> Any

Return time grid for variable time problems (times are then dependent on NLP variables)

is_solvable(ocp) -> Bool

Check if an OCP is solvable by the method solve.

model(docp::CTDirect.DOCP) -> Any

Extracts the NLP model from a DOCP object.

Arguments

• docp::DOCP: The DOCP object containing the NLP model.

Returns

The NLP model stored in the DOCP object.

setPointConstraints!(docp::CTDirect.DOCP, c, xu, v) -> Any

Set the boundary and variable constraints

variables_bounds!(
    docp::CTDirect.DOCP
) -> Tuple{Vector{Float64}, Vector{Float64}}

Build upper and lower bounds vectors for the DOCP variable box constraints.