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Suppose that we wish to find the function
which
maximizes or minimizes the functional
 |
(E.17) |
subject to the constraint that the value of
 |
(E.18) |
remains constant. We can achieve our goal by finding an extremum of the new functional
, where
is an undetermined function. We know
that
, because the value of
is fixed, so if
then
as well. In other words, finding an extremum of
is equivalent
to finding an extremum of
. Application of the Euler-Lagrange
equation yields
![$\displaystyle \frac{d}{dx}\!\left(\frac{\partial F}{\partial y'}\right)-\frac{\...
...da\,G]}{\partial y'}\right)-\frac{\partial [\lambda\,G]}{\partial y}\right]= 0.$](img7337.png) |
(E.19) |
In principle, the previous equation, together with the constraint (E.18),
yields the functions
and
. Incidentally,
is generally
termed a Lagrange multiplier. If
and
have no explicit
-dependence then
is usually a constant.
As an example, consider the following famous problem. Suppose that a uniform
chain of fixed length
is suspended by its ends from
two equal-height fixed points that are a distance
apart, where
.
What is the equilibrium configuration of the chain?
Suppose that the chain has the uniform density per unit length
.
Let the
- and
-axes be horizontal and vertical, respectively, and
let the two ends of the chain lie at
. The equilibrium configuration of the chain is specified by the function
, for
, where
is the vertical distance of the chain below its end points at horizontal
position
. Of course,
.
According to standard Newtonian dynamics, the stable equilibrium
state of a conservative dynamical system is one that minimizes
the system's potential energy (Fitzpatrick 2012). Now, the potential energy of the chain
is written
 |
(E.20) |
where
is an element of length along the chain, and
is the acceleration due to gravity.
Hence, we need to minimize
with respect to small variations in
.
However, the variations in
must be such as to conserve the
fixed length of the chain. Hence, our minimization procedure is subject to
the constraint that
 |
(E.21) |
remains constant.
It follows, from the previous discussion, that we need to minimize the
functional
 |
(E.22) |
where
is an, as yet, undetermined constant. Because the integrand
in the functional does not depend explicitly on
, we have
from Equation (E.14) that
 |
(E.23) |
where
is a constant. This expression reduces to
 |
(E.24) |
where
, and
.
Let
 |
(E.25) |
Making this substitution, Equation (E.24) yields
 |
(E.26) |
Hence,
 |
(E.27) |
where
is a constant. It follows from Equation (E.25) that
![$\displaystyle y(x) =-h\,[\lambda' + \cosh(-x/h + c)].$](img7353.png) |
(E.28) |
The previous solution contains three undetermined constants,
,
, and
. We can
eliminate two of these constants by application of the boundary
conditions
. This yields
 |
(E.29) |
Hence,
, and
. It follows that
![$\displaystyle y(x) = h\,[\cosh(a/2\,h) - \cosh(x/h)].$](img7359.png) |
(E.30) |
The final unknown constant,
, is determined via the application of
the constraint (E.21). Thus,
 |
(E.31) |
Hence, the equilibrium configuration of the chain is given by the curve
(E.30), which is known as a catenary (from the Latin for chain), where the parameter
satisfies
 |
(E.32) |
Next: Multi-Function Variation
Up: Calculus of Variations
Previous: Euler-Lagrange Equation
Richard Fitzpatrick
2016-03-31