tuto update (jb)

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"

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",

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
 <img width="200" alt="affiliations" src="./assets/france-2030.png">
-```
+```

docs/src/tutorial_mam.md → 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
 ```