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Merge pull request #149 from control-toolbox/quickfix
Quickfix
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docs/src/juliacon2023.md

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@@ -52,10 +52,9 @@ plus boundary, control and state constraints
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# Credits (not exhaustive!)
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- [DifferentialEquations.jl](https://github.com/SciML/DifferentialEquations.jl)
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- [JuliaSmoothOptimizers](https://github.com/JuliaSmoothOptimizers)
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([JuMP](https://jump.dev/JuMP.jl),
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- [JuMP](https://jump.dev/JuMP.jl),
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[InfiniteOpt.jl](https://docs.juliahub.com/InfiniteOpt/p3GvY/0.4.1),
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[ADNLPModels.jl](https://jso.dev/ADNLPModels.jl))
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[ADNLPModels.jl](https://jso.dev/ADNLPModels.jl)
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- [Ipopt](https://github.com/coin-or/ipopt)
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- [JuliaDiff](https://juliadiff.org)
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([FowardDiff.jl](https://juliadiff.org/ForwardDiff.jl),

docs/src/tutorial-basic-example-f.md

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@@ -43,17 +43,14 @@ using OptimalControl
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Then, we can define the problem
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```@example main
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t0 = 0
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tf = 1
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A = [ 0 1
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0 0 ]
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B = [ 0
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1 ]
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ocp = Model()
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time!(ocp, [t0, tf])
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time!(ocp, [ 0, 1 ])
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state!(ocp, 2)
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control!(ocp, 1)
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docs/src/tutorial-basic-example.md

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@@ -43,15 +43,12 @@ using OptimalControl
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Then, we can define the problem
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```@example main
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t0 = 0
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tf = 1
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@def ocp begin
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t ∈ [ t0, tf ], time
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t ∈ [ 0, 1 ], time
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x ∈ R², state
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u ∈ R, control
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x(t0) == [-1, 0]
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x(tf) == [0, 0]
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x(0) == [-1, 0]
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x(1) == [0, 0]
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ẋ(t) == A * x(t) + B * u(t)
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∫( 0.5u(t)^2 ) → min
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end

src/OptimalControl.jl

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@@ -52,6 +52,7 @@ export is_time_independent, is_time_dependent, is_min, is_max, is_variable_depen
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export Lie, @Lie, Poisson, Lift, , ∂ₜ
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export @def
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export ct_repl
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export ParsingError
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# CTProblems
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export ProblemsDescriptions, Problem, Problems, @ProblemsDescriptions, @Problems

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