I just wrote this

OptimalControl.jl/docs/src/manual-solve.md

Line 84 in 0497d90

    
           - `:exa`: the NLP problem is modeled by a [`ExaModels.ExaModel`](@extref). It provides automatic differentiation and [SIMD](https://en.wikipedia.org/wiki/Single_instruction,_multiple_data) abstraction.

and this

OptimalControl.jl/docs/src/manual-solve.md

Lines 90 to 112 in 0497d90

    
           !!! warning 
        
               The dynamics must be defined coordinatewise to use ExaModels.jl (`:exa`). 
        
           For instance, let us try MadNLP solver with ExaModel modeller. 
        
           ```@example main 
        
           using MadNLP 
        
           ocp = @def begin 
        
               t ∈ [ t0, tf ], time 
        
               x = (q, v) ∈ R², state 
        
               u ∈ R, control 
        
               x(t0) == x0 
        
               x(tf) == [0, 0] 
        
               ∂(q)(t) == v(t) 
        
               ∂(v)(t) == u(t) 
        
               0.5∫( u(t)^2 ) → min 
        
           end 
        
           solve(ocp, :exa, :madnlp) 
        
           nothing # hide 
        
           ```

	!!! warning

	The dynamics must be defined coordinatewise to use ExaModels.jl (`:exa`).

	For instance, let us try MadNLP solver with ExaModel modeller.

	```@example main
	using MadNLP

	ocp = @def begin
	t ∈ [ t0, tf ], time
	x = (q, v) ∈ R², state
	u ∈ R, control
	x(t0) == x0
	x(tf) == [0, 0]
	∂(q)(t) == v(t)
	∂(v)(t) == u(t)
	0.5∫( u(t)^2 ) → min
	end

	solve(ocp, :exa, :madnlp)
	nothing # hide
	```

Solve documentation #305

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