diff --git a/docs/Project.toml b/docs/Project.toml index 514b94a37..16d5ae897 100644 --- a/docs/Project.toml +++ b/docs/Project.toml @@ -17,7 +17,6 @@ MINPACK = "4854310b-de5a-5eb6-a2a5-c1dee2bd17f9" MadNLP = "2621e9c9-9eb4-46b1-8089-e8c72242dfb6" NLPModelsIpopt = "f4238b75-b362-5c4c-b852-0801c9a21d71" NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec" -OptimalControl = "5f98b655-cc9a-415a-b60e-744165666948" OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed" Percival = "01435c0c-c90d-11e9-3788-63660f8fbccc" Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80" diff --git a/docs/make.jl b/docs/make.jl index 199e58146..cde5b2387 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -46,9 +46,9 @@ makedocs(; "Discrete continuation" => "tutorial-continuation.md", "NLP options" => "tutorial-nlp.md", "Goddard: direct, indirect" => "tutorial-goddard.md", - "tutorial-iss.md", + "Indirect simple shooting" => "tutorial-iss.md", "Linear–quadratic regulator" => "tutorial-lqr-basic.md", - "Minimal action" => "tutorial_mam.md", + "Minimal action" => "tutorial-mam.md", ], "Developers" => [ "OptimalControl.jl" => "dev-optimalcontrol.md", diff --git a/docs/src/juliacon2024.md b/docs/src/juliacon2024.md index 9d35a436e..fc93a8690 100644 --- a/docs/src/juliacon2024.md +++ b/docs/src/juliacon2024.md @@ -24,7 +24,7 @@ subject to \dot{x}(t) = f(x(t), u(t)),\quad t \in [t_0, t_f] ``` -plus boundary, control and state constraints +plus boundary conditions, control and state constraints - Our core interests: numerical & geometrical methods in control, applications @@ -68,4 +68,4 @@ Jean-Baptiste Caillau is partially funded by a **France 2030** support managed b ```@raw html affiliations -``` +``` \ No newline at end of file diff --git a/docs/src/tutorial_mam.md b/docs/src/tutorial-mam.md similarity index 99% rename from docs/src/tutorial_mam.md rename to docs/src/tutorial-mam.md index f4ccbf98c..ed01898eb 100644 --- a/docs/src/tutorial_mam.md +++ b/docs/src/tutorial-mam.md @@ -112,7 +112,7 @@ println(" Time Objective Iterations") for T=Ts global sol = solve(ocp(T); display=false, init=sol, grid_size=1000, tol=1e-8) @printf("%6.2f %9.6e %d\n", T, objective(sol), iterations(sol)) - push!(objectives, sol.objective) + push!(objectives, objective(sol)) end ```