diff --git a/dev/.documenter-siteinfo.json b/dev/.documenter-siteinfo.json index a5f9336..aebc0c4 100644 --- a/dev/.documenter-siteinfo.json +++ b/dev/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.10.3","generation_timestamp":"2024-05-05T20:06:05","documenter_version":"1.4.1"}} \ No newline at end of file +{"documenter":{"julia_version":"1.10.3","generation_timestamp":"2024-05-05T20:06:45","documenter_version":"1.4.1"}} \ No newline at end of file diff --git a/dev/api.html b/dev/api.html index 7b3b365..892f42e 100644 --- a/dev/api.html +++ b/dev/api.html @@ -11,7 +11,7 @@ kwargs_Flow... ) -> CTFlows.OptimalControlFlow

Flow from an optimal control problem, a control function in feedback form, a state constraint and its associated multiplier in feedback form.

Example

julia> ocp = Model(autonomous=false)
-julia> f = Flow(ocp, (t, x, p) -> p[1], (t, x, u) -> x[1] - 1, (t, x, p) -> x[1]+p[1])
Warning

The time dependence of the control function must be consistent with the time dependence of the optimal control problem. The dimension of the output of the control function must be consistent with the dimension usage of the control of the optimal control problem.

source
CTFlows.Flow — Method
Flow(
+julia> f = Flow(ocp, (t, x, p) -> p[1], (t, x, u) -> x[1] - 1, (t, x, p) -> x[1]+p[1])
Warning

The time dependence of the control function must be consistent with the time dependence of the optimal control problem. The dimension of the output of the control function must be consistent with the dimension usage of the control of the optimal control problem.

source
CTFlows.Flow — Method
Flow(
     ocp::CTBase.OptimalControlModel{T, V},
     u_::Union{CTBase.ControlLaw{T, V}, Function};
     alg,
@@ -20,4 +20,4 @@
     saveat,
     kwargs_Flow...
 ) -> CTFlows.OptimalControlFlow
-

Flow from an optimal control problem and a control function in feedback form.

Example

julia> f = Flow(ocp, (x, p) -> p)
Warning

The time dependence of the control function must be consistent with the time dependence of the optimal control problem. The dimension of the output of the control function must be consistent with the dimension usage of the control of the optimal control problem.

source
+

Flow from an optimal control problem and a control function in feedback form.

Example

julia> f = Flow(ocp, (x, p) -> p)
Warning

The time dependence of the control function must be consistent with the time dependence of the optimal control problem. The dimension of the output of the control function must be consistent with the dimension usage of the control of the optimal control problem.

source diff --git a/dev/dev-api.html b/dev/dev-api.html index 93fcafe..45b0bc8 100644 --- a/dev/dev-api.html +++ b/dev/dev-api.html @@ -2,22 +2,22 @@ Developers · CTFlows.jl
GitHub

Internal functions

CTBase.OptimalControlSolution — Method
OptimalControlSolution(
     ocfs::CTFlows.OptimalControlFlowSolution
 ) -> CTBase.OptimalControlSolution
-

Construct an OptimalControlSolution from an OptimalControlFlowSolution.

source
CTFlows.OptimalControlFlowSolution — Type
struct OptimalControlFlowSolution

Type of an optimal control flow solution.

Fields

  • ode_sol::Any

  • feedback_control::CTBase.ControlLaw

  • ocp::CTBase.OptimalControlModel

  • variable::Union{Real, AbstractVector{<:Real}}

source
CTFlows.__abstol — Method
__abstol() -> Float64
-

Default absolute tolerance for ODE solvers.

See abstol from OrdinaryDiffEq.

source
CTFlows.__alg — Method
__alg(
+

Construct an OptimalControlSolution from an OptimalControlFlowSolution.

source
CTFlows.OptimalControlFlowSolution — Type
struct OptimalControlFlowSolution

Type of an optimal control flow solution.

Fields

  • ode_sol::Any

  • feedback_control::CTBase.ControlLaw

  • ocp::CTBase.OptimalControlModel

  • variable::Union{Real, AbstractVector{<:Real}}

source
CTFlows.__abstol — Method
__abstol() -> Float64
+

Default absolute tolerance for ODE solvers.

See abstol from OrdinaryDiffEq.

source
CTFlows.__alg — Method
__alg(
 
 ) -> OrdinaryDiffEq.Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}
-

Default algorithm for ODE solvers.

See alg from OrdinaryDiffEq.

source
CTFlows.__reltol — Method
__reltol() -> Float64
-

Default relative tolerance for ODE solvers.

See reltol from OrdinaryDiffEq.

source
CTFlows.__reltol — Method
__reltol() -> Float64
+

Default relative tolerance for ODE solvers.

See reltol from OrdinaryDiffEq.

source
CTFlows.hamiltonian_usage — Method
hamiltonian_usage(
     alg,
     abstol,
     reltol,
     saveat;
     kwargs_Flow...
 ) -> Any
-

Returns a function that solves ODE problem associated to Hamiltonian vector field.

source
CTFlows.makeH — Method
makeH(
+

Returns a function that solves ODE problem associated to Hamiltonian vector field.

source
CTFlows.makeH — Method
makeH(
     f::CTBase.Dynamics,
     u::CTBase.ControlLaw,
     f⁰::CTBase.Lagrange,
@@ -26,38 +26,38 @@
     g::CTBase.MixedConstraint,
     μ::CTBase.Multiplier
 ) -> CTFlows.var"#H#68"{CTBase.Dynamics{time_dependence, variable_dependence}, CTBase.ControlLaw{time_dependence1, variable_dependence1}, CTBase.Lagrange{time_dependence2, variable_dependence2}, var"#s178", var"#s1781", CTBase.MixedConstraint{time_dependence3, variable_dependence3}, CTBase.Multiplier{time_dependence4, variable_dependence4}} where {time_dependence, variable_dependence, time_dependence1, variable_dependence1, time_dependence2, variable_dependence2, var"#s178"<:Real, var"#s1781"<:Real, time_dependence3, variable_dependence3, time_dependence4, variable_dependence4}
-

Constructs the Hamiltonian:

H(t, x, p) = p ⋅ f(t, x, u(t, x, p)) + s p⁰ f⁰(t, x, u(t, x, p)) + μ(t, x, p) ⋅ g(t, x, u(t, x, p))

source
CTFlows.makeH — Method
makeH(
+

Constructs the Hamiltonian:

H(t, x, p) = p ⋅ f(t, x, u(t, x, p)) + s p⁰ f⁰(t, x, u(t, x, p)) + μ(t, x, p) ⋅ g(t, x, u(t, x, p))

source
CTFlows.makeH — Method
makeH(
     f::CTBase.Dynamics,
     u::CTBase.ControlLaw,
     f⁰::CTBase.Lagrange,
     p⁰::Real,
     s::Real
 ) -> CTFlows.var"#H#66"{CTBase.Dynamics{time_dependence, variable_dependence}, CTBase.ControlLaw{time_dependence1, variable_dependence1}, CTBase.Lagrange{time_dependence2, variable_dependence2}, <:Real, <:Real} where {time_dependence, variable_dependence, time_dependence1, variable_dependence1, time_dependence2, variable_dependence2}
-

Constructs the Hamiltonian:

H(t, x, p) = p ⋅ f(t, x, u(t, x, p)) + s p⁰ f⁰(t, x, u(t, x, p))

source
CTFlows.makeH — Method
makeH(
+

Constructs the Hamiltonian:

H(t, x, p) = p ⋅ f(t, x, u(t, x, p)) + s p⁰ f⁰(t, x, u(t, x, p))

source
CTFlows.makeH — Method
makeH(
     f::CTBase.Dynamics,
     u::CTBase.ControlLaw,
     g::CTBase.MixedConstraint,
     μ::CTBase.Multiplier
 ) -> CTFlows.var"#H#67"{CTBase.Dynamics{time_dependence, variable_dependence}, CTBase.ControlLaw{time_dependence1, variable_dependence1}, CTBase.MixedConstraint{time_dependence2, variable_dependence2}, CTBase.Multiplier{time_dependence3, variable_dependence3}} where {time_dependence, variable_dependence, time_dependence1, variable_dependence1, time_dependence2, variable_dependence2, time_dependence3, variable_dependence3}
-

Constructs the Hamiltonian:

H(t, x, p) = p ⋅ f(t, x, u(t, x, p)) + μ(t, x, p) ⋅ g(t, x, u(t, x, p))

source
CTFlows.makeH — Method
makeH(
+

Constructs the Hamiltonian:

H(t, x, p) = p ⋅ f(t, x, u(t, x, p)) + μ(t, x, p) ⋅ g(t, x, u(t, x, p))

source
CTFlows.makeH — Method
makeH(
     f::CTBase.Dynamics,
     u::CTBase.ControlLaw
 ) -> CTFlows.var"#64#65"{CTBase.Dynamics{time_dependence, variable_dependence}, CTBase.ControlLaw{time_dependence1, variable_dependence1}} where {time_dependence, variable_dependence, time_dependence1, variable_dependence1}
-

Constructs the Hamiltonian:

H(t, x, p) = p f(t, x, u(t, x, p))

source
CTFlows.ode_usage — Method
ode_usage(
     alg,
     abstol,
     reltol,
     saveat;
     kwargs_Flow...
 ) -> Any
-

Returns a function that solves any ODE problem with OrdinaryDiffEq.

source
CTFlows.rhs — Method
rhs(
+

Returns a function that solves any ODE problem with OrdinaryDiffEq.

source
CTFlows.rhs — Method
rhs(
     h::CTBase.AbstractHamiltonian
 ) -> CTFlows.var"#rhs!#24"{<:CTBase.AbstractHamiltonian{time_dependence, variable_dependence}} where {time_dependence, variable_dependence}
-

The right and side from a Hamiltonian.

source
CTFlows.vector_field_usage — Method
vector_field_usage(
     alg,
     abstol,
     reltol,
     saveat;
     kwargs_Flow...
 ) -> Any
-

Returns a function that solves ODE problem associated to classical vector field.

source
+

Returns a function that solves ODE problem associated to classical vector field.

source diff --git a/dev/objects.inv b/dev/objects.inv index 58dd2c6..2297773 100644 Binary files a/dev/objects.inv and b/dev/objects.inv differ