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Merge pull request #569 from control-toolbox/562-doc-relecture-de-la-documentation
Relecture documentation
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docs/src/manual-abstract.md

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@@ -257,7 +257,7 @@ In the example below, there are
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(t) == [x₂(t), u(t)]
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tf 0
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x₂(t) 1
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u(t)^2 1
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0.1 u(t)^2 1
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...
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end
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```
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(t) == [x₂(t), u(t)]
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tf >= 0
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x₂(t) <= 1
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u(t)^2 <= 1
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0.1 u(t)^2 <= 1
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...
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end
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```

docs/src/manual-flow-ocp.md

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The **pseudo-Hamiltonian** of this problem is
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```math
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H(x, p, u) = p_q\, q + p_v\, v + p^0 u^2 /2,
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H(x, p, u) = p_q\, v + p_v\, u + p^0 u^2 /2,
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```
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where $p^0 = -1$ since we are in the normal case. From the Pontryagin maximum principle, the maximising control is given in feedback form by

docs/src/manual-flow-others.md

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Consider the simple optimal control problem from the [basic example page](@ref example-double-integrator-energy). The **pseudo-Hamiltonian** is
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```math
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H(x, p, u) = p_q\, q + p_v\, v + p^0 u^2 /2,
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H(x, p, u) = p_q\, v + p_v\, u + p^0 u^2 /2,
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```
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where $p^0 = -1$ since we are in the normal case. From the Pontryagin maximum principle, the maximising control is given in feedback form by
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where $x=(q,v)$, $p=(p_q,p_v)$, $p^0 = -1$ since we are in the normal case. From the Pontryagin maximum principle, the maximising control is given in feedback form by
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```math
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u(x, p) = p_v

docs/src/manual-model.md

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You can also compute flows (for more details, see the [flow manual](@ref manual-flow-ocp)) from the optimal control problem, providing a control law in feedback form. The **pseudo-Hamiltonian** of this problem is
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```math
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H(x, p, u) = p_q\, q + p_v\, v + p^0 u^2 /2,
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H(x, p, u) = p_q\, v + p_v\, u + p^0 u^2 /2,
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```
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where $p^0 = -1$ since we are in the normal case. From the Pontryagin maximum principle, the maximising control is given in feedback form by

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