Lagrange's Foramlism for Classical Mechanics
Hamilton's principle
Hamilton's principle falls out of the calculus of variations in that seeking the shortest time interval is the focus of the variations.
- Of all possible paths along which a dynamical system may move from on point to another within a specified time interval, the actual path followed is that which minimizes the time integral of the difference between the kinetic and potential energies.
Casting this in the language of the calculus of variations
- [math]S \equiv \int_{t_1}^{t_2} \left ( T(\dot x) - U(x) \right ) dt = \int_{t_1}^{t_2} f(x,\dot x ; t) dt = \int_{t_1}^{t_2} \mathcal {L} ( x, \dot x;t) dt [/math]
if you want the above "action" integral to be stationary then according to the calculus of variations you want the Euler-Lagrange equation to be satisfied where
- [math] \left [ \left ( \frac{\partial f}{\partial x} \right ) - \frac{d}{dt} \left ( \frac{\partial f}{\partial \dot x} \right ) \right ] =0 [/math]
or
- [math] \left [ \left ( \frac{\partial \mathcal {L} }{\partial x} \right ) - \frac{d}{dt} \left ( \frac{\partial \mathcal {L} }{\partial \dot x} \right ) \right ] =0 [/math]
here [math]x^{\prime} = \frac{d x}{d t} \equiv \dot x[/math]
- [math] \left ( \frac{\partial \mathcal {L} }{\partial x} \right ) = \frac{\partial }{\partial x} \left ( T(\dot x) - U(x) \right ) = -\frac{\partial U(x)}{\partial x} = F_x[/math] the generalized force if I have conservative forces
- [math] \frac{d}{dt} \left ( \frac{\partial \mathcal {L} }{\partial \dot x} \right ) = \frac{d}{dt} \left ( \frac{\partial }{\partial \dot x} \right ) \left ( T(\dot x) - U(x) \right ) [/math]
- [math] = \frac{d}{dt} \left ( \frac{\partial }{\partial \dot x} \right ) T(\dot x) = \frac{d}{dt} m \dot x = \frac{d}{dt} p_x = \dot{p}_x = F_x [/math] Newton's second law in an Inertial reference frame = time derivative of the generalized momentum
thus
- [math] \left [ \left ( \frac{\partial \mathcal {L} }{\partial x} \right ) - \frac{d}{dt} \left ( \frac{\partial \mathcal {L} }{\partial \dot x} \right ) \right ] = F_x - F_x = 0 [/math]
Lagrange's Equations in generalized coordinates
Generalized coordinates [math](q_i)[/math] are a set of parameters that uniquely specify the instantaneous state of a dynamical system.
The number of independent generalized coordinates [math](N_q)[/math] is given by subtracting the number of constraints [math](N_C)[/math] from the number of degrees of freedom [math]N_{DF}[/math].
- [math]N_q = N_{DF} - N_C[/math]
Pedulum example
Consider the 2-D pendulum where an object of mass [math]m[/math] is constrained by a rod of length [math]l[/math]. The object is at one end of the rod and the rod is fixed to rotate about the other end.
- [math]N_{DF} =2 [/math] There are 32 degrees of freedom for the 2-D problem
- [math] N_C =1 [/math] The particle is constrained to a rod
- [math]N_q = 2-1 = 1 [/math] The motion of the particle may be described using one component
The constraint may be expressed in cartesian coordinates as
- [math] x^2 + y^2 = l^2[/math]
you can express the position of the object on the end of a rod as a function of just one generalized coordinate
- [math]\vec r = x \hat i + y \hat j = x \hat i + \sqrt{l^2-x^2} \hat j = \vec r(x)[/math] [math]x[/math] is the generalized coordinate
You could also express the position as a function of the deflection angle [math]\phi[/math] in cartesian coordinates
- [math]\vec r = l \cos \phi \hat i + l \sin \phi \hat j = \vec r (\phi)[/math] [math]\phi[/math] is the generalized coordinate
- Note
- If you were to start using Polar coordinates right away such that
- [math]\vec r = l \hat r[/math]
then the dependence of the function on [math]\phi[/math] would not be obvious as this dependence is implicit to changes in the [math]\hat r[/math] direction
The number of generalized coordinates becomes more obvious when you begin expressing the Potential and Kinetic Energy
- [math]U = mgh = l( 1-\cos \phi)[/math]
- [math] T = \frac{1}{2} m v^2 = \frac{1}{2} l^2 \dot \phi^2[/math]
Motion on Sphere example
Consider a particle constrained to move on a sphere of radius [math]R[/math].
- [math]N_{DF} =3 [/math] There are 3 degrees of freedom for the 3-D problem
- [math] N_C =1 [/math] The particle is constrained to the surface of the sphere
- [math]N_q = 3-1 = 2 [/math] The motion of the particle may be described using two components
The constraint expressed in terms of cartesian coordinates is
- [math] x^2 + y^2 + z^2 = R^2[/math]
The above constraint equation can be used to reduce the degrees of freedom by using the constraint to eliminate one of the above components
for Example
- [math] z^2 = R^2-x^2 - y^2[/math]
- [math]\vec r = x \hat i + y \hat j \pm \sqrt{R^2-x^2 - y^2} \hat k = \vec r ( x,y)[/math]
or if you chose the angles [math]\theta[/math] and [math]\phi[/math] from spherical coordinates
- [math] \vec r = R \cos \phi \sin \theta \hat i + R \sin \phi \sin \theta \hat j + R \cos \theta \hat k = \vec r (\phi, \theta) [/math]
Generalized Force and Momentum
- Generalized Force [math]\equiv \frac{\partial \mathcal {L} }{\partial q}[/math]
- Generalized Momentum [math]\equiv \frac{\partial \mathcal {L} }{\partial \dot q}[/math]
As shown above, Hamilton's principle leads to a re-expression of Newton's second law through the Euler-Lagrange Equation in a differential form known as Lagrange's equations.
Below is the Euler-Lagrange equations expressed in terms of generalized coordinates.
- [math] \left [ \left ( \frac{\partial \mathcal {L} }{\partial q} \right ) = \frac{d}{dt} \left ( \frac{\partial \mathcal {L} }{\partial \dot q} \right ) \right ] [/math]
Example: Lagrangian for object in 2-D moving in a conservative field
In cartesian coordinates
- [math]\mathcal L = T - U = \left ( \frac{1}{2} m(\dot x^2 + \dot y^2) \right ) - \left ( U(x,y) \right ) [/math]
- [math] \frac{\partial \mathcal {L} }{\partial q} \right = \frac{d}{dt} \left ( \frac{\partial \mathcal {L} }{\partial \dot q} \right ) [/math]
- for the generalized coordinate labeled [math]x[/math]
- [math] \frac{\partial \mathcal {L} }{\partial x} = - \frac{\partial U }{\partial x} = \frac{d}{dt} \left ( \frac{\partial \mathcal {L} }{\partial \dot x} \right ) = \frac{d}{dt}m \dot x = m\ddot x[/math]
- for the generalized coordinate labeled [math]y[/math]
- [math] \frac{\partial \mathcal {L} }{\partial q} = \frac{d}{dt} \left ( \frac{\partial \mathcal {L} }{\partial \dot q} \right ) [/math]
In polar coordinates
- [math] \left ( \frac{\partial \mathcal {L} }{\partial q} \right ) = \frac{d}{dt} \left ( \frac{\partial \mathcal {L} }{\partial \dot q} \right ) [/math]
- [math] \frac{\partial \mathcal {L} }{\partial q} = \frac{d}{dt} \left ( \frac{\partial \mathcal {L} }{\partial \dot q} \right ) [/math]
- [math] \frac{\partial \mathcal {L} }{\partial q} = \frac{d}{dt} \left ( \frac{\partial \mathcal {L} }{\partial \dot q} \right ) [/math]
Forest_Ugrad_ClassicalMechanics