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Overall looks good to me.
Please make sure you follow Julia's conventions:
- ensure that the indentations remain consistent (always use 4 spaces to indent, do not mix the indentations in the same file)
- add unit-tests in
testto check if the problems are well defined and run to optimality with Ipopt
…olbox/OptimalControlProblems.jl into 4-dev-add-cots-models
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@0Yassine0 Check this tutorial: https://control-toolbox.org/OptimalControl.jl/stable/tutorial-nlp.html ocp = @def begin
t ∈ [0, 1], time
x ∈ R², state
u ∈ R, control
x(0) == [ -1, 0 ]
x(1) == [ 0, 0 ]
ẋ(t) == [ x₂(t), u(t) ]
∫( 0.5u(t)^2 ) → min
end
docp, nlp = direct_transcription(ocp)
using NLPModelsIpopt
nlp_sol = ipopt(nlp; print_level=5, mu_strategy="adaptive", tol=1e-8, sb="yes") |
ocots
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ocots
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@0Yassine0 tells me when the PR is ready for review, it looks like you are still doing some updates |
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ocots
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frapac
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LGTM.
I would suggest to use "Squash & Merge" to merge this PR in main, to keep a clean git history.
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I just extended the time limit because the quadrator problem passes the test in a bit more time then set. |
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