Theorem: Necessary Condition for Integral Functional to have Extremum for given function/Dependent on N Functions

Let $\mathbf y$ be an $n$-dimensional real vector.
Let $J \sqbrk {\mathbf y}$ be a functional of the form:
$\ds J \sqbrk {\mathbf y} = \int_a^b \map F {x, \mathbf y, \mathbf y'} \rd x$
Let:
:$\mathbf y \in C^1 \closedint a b$
where $C^1 \closedint a b$ denotes that $\mathbf y$ is continuously differentiable in $\closedint a b$
Let $\mathbf y$ satisfy boundary conditions:
:$\map {\mathbf y} a = \mathbf A$ 
:$\map {\mathbf y} b = \mathbf B$
where $\mathbf A$, $\mathbf B$ are real vectors.
Then a necessary condition for $J \sqbrk {\mathbf y}$ to have an extremum (strong or weak) for a given $\mathbf y$ is that they satisfy Euler's equations:
$F_{\mathbf y} - \dfrac \d {\d x} F_{\mathbf y'} = 0$

Proof:
From Condition for Differentiable Functional of N Functions to have Extremum:
:$\ds \bigvalueat {\delta J \sqbrk {\mathbf y; \mathbf h} } {\mathbf y \mathop = \hat{\mathbf y} } = 0$
For the variation to exist it has to satisfy the requirement for a differentiable functional.
Note that the endpoints of $\map {\mathbf y} x$ are fixed. $\map {\mathbf h} x$ is not allowed to change values of $\map {\mathbf y} x$ at those points.
Hence $\map {\mathbf h} a = 0$ and $\map {\mathbf h} b = 0$.
We will start from the increment of a functional:
{{begin-eqn}}
{{eqn | l = \Delta J \sqbrk {\mathbf y; \mathbf h}
      | r = J \sqbrk {\mathbf y + \mathbf h} - J \sqbrk {\mathbf y}
}}
{{eqn | r = \int_a^b \map F {x, \mathbf y + \mathbf h, \mathbf y' + \mathbf h'} \rd x - \int_a^b \map F {x, \mathbf y, \mathbf y'} \rd x
}}
{{eqn | r = \int_a^b \paren {\map F {x, \mathbf y + \mathbf h, \mathbf y' + \mathbf h'} - \map F {x, \mathbf y, \mathbf y'} } \rd x
}}
{{end-eqn}}
Using multivariate Taylor's theorem, one can expand $\map F {x, \mathbf y + \mathbf h, \mathbf y' + \mathbf h'}$ with respect to functions $\map {\mathbf h} x$ and $\map {\mathbf h'} x$:
{{begin-eqn}}
{{eqn | l = \map F {x, \mathbf y + \mathbf h, \mathbf y' + \mathbf h'}
      | r = \bigvalueat {\map F {x, \mathbf y + \mathbf h, \mathbf y' + \mathbf h'} } {\mathbf h \mathop = \mathbf 0, \mathbf h' \mathop = \mathbf 0}
      | c = 
}}
{{eqn | o = 
      | ro= +
      | r = \valueat {\sum_{i \mathop = 1}^n \frac {\partial {\map F {x, \mathbf y + \mathbf h, \mathbf y' + \mathbf h'} } } {\partial {y_i} } } {h_i \mathop = 0, h_i' \mathop = 0} h_i
      | c = 
}}
{{eqn | o = 
      | ro= +
      | r = \valueat {\sum_{i \mathop = 1}^n \frac {\partial {\map F {x, \mathbf y + \mathbf h, \mathbf y + \mathbf h} } } {\partial {y_i}'} } {h_i \mathop = 0, h_i' \mathop = 0} {h_i}'
      | c = 
}}
{{eqn | o = 
      | ro= +
      | r = \map \OO {h_i h_j, h_i h_j', h_i' h_j'}
      | c = for $i, j \in \openint 1 n$
}}
{{end-eqn}}
We can substitute this back into the integral.
Note that the first term in the expansion and the negative one in the integral will cancel out.
Hence:
:$\ds \Delta J \sqbrk {\mathbf y; \mathbf h} = \int_a^b \sum_{i \mathop = 1}^n \paren {F_{y_i} h_i + F_{y_i'} h_i' + \map \OO {h_i h_j,h_i h_j',h_i' h_j'} } \rd x$ for $i, j \in \openint 1 n$
{{Explain|Finish single function case, then return here}}
By definition, the integral not counting in $\map \OO {h_i h_j,h_i h_j',h_i' h_j'}$ for $i, j \in \openint 1 n$ is a variation of functional:
{{explain|The link is to Definition:Differentiable Functional but the label says "variation of functional" which is not defined on that page}}
:$\ds \delta J \sqbrk {\mathbf y; \mathbf h} = \int_a^b \paren {F_{\mathbf y} \mathbf h + F_{\mathbf y'} \mathbf h'} \rd x$
The variation vanishes if for all functions $h_i$ every term containing $h_i$ vanishes independently.
Therefore, we discover a set of Euler's Equations being satisfied simultaneously:
:$F_{\mathbf y} - \dfrac \d {\d x} F_{\mathbf y'} =  0$
{{qed}}
{{improve|find a better way to deal with notation of dependence on multiple functions (probably through mapping to avoid explicit arguments); build related pages}}