Proving Euler-Lagrange for constrained system

In summary, we discussed how constrained generalized coordinates contribute to reducing the degree of freedom in a system, and how we can propose a Lagrangian that takes into account these constraints. We also discussed how we can show that this proposed Lagrangian is Euler-Lagrange by deriving the equations of motion.
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Homework Statement



Given two Euler-Lagrange systems with generalized coordinates ##r_1## and ##r_2,## and input ##u_1## and ##u_2##. Suppose now that a constraint is placed on them such that ##r_1 = f_1(q)## and ##r_2 = f_2(q)##.

Propose a Lagrangian for the constrained system and show that is is also Euler-Lagrange

Homework Equations


Where should I even be starting on this type of proof?

The Attempt at a Solution


I do know that the generalized coordinate themselves are constrained now, but do they contribute at all to reducing the degree of freedom?
 
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Hello, great question! Yes, the constrained generalized coordinates do contribute to reducing the degree of freedom in the system. This is because the constraint equations ##r_1 = f_1(q)## and ##r_2 = f_2(q)## effectively eliminate two degrees of freedom from the original system. This means that the Lagrangian for the constrained system must also take into account these constraints in order to accurately describe the dynamics of the system.

To propose a Lagrangian for the constrained system, we can start with the original Lagrangian for the unconstrained system and add in terms that take into account the constraints. For example, we can add a term ##\lambda_1 (r_1 - f_1(q))## to the Lagrangian, where ##\lambda_1## is a Lagrange multiplier. This term ensures that the constraint ##r_1 = f_1(q)## is satisfied in the dynamics of the system. Similarly, we can add a term ##\lambda_2 (r_2 - f_2(q))## to take into account the second constraint.

To show that this proposed Lagrangian is also Euler-Lagrange, we can use the same method as for an unconstrained system. We can derive the equations of motion using the constrained Lagrangian and show that they are equivalent to the equations of motion derived from the original unconstrained Lagrangian. This will demonstrate that the proposed Lagrangian accurately describes the dynamics of the constrained system.

I hope this helps! Let me know if you have any further questions.
 

FAQ: Proving Euler-Lagrange for constrained system

1. What is Euler-Lagrange for constrained system?

Euler-Lagrange for constrained system is a mathematical framework used to find the equations of motion of a system with constraints. It is based on the principle of least action, where the system's motion is described by minimizing the action integral.

2. How is Euler-Lagrange for constrained system different from unconstrained systems?

In unconstrained systems, the equations of motion can be derived directly from the Lagrangian. However, in constrained systems, the constraints must be taken into account and the equations of motion are found by using the Euler-Lagrange equations with Lagrange multipliers.

3. What are the assumptions made in Euler-Lagrange for constrained system?

The main assumptions made in Euler-Lagrange for constrained system are that the system is conservative, the constraints are holonomic, and the constraints are independent. These assumptions allow for the use of the Lagrangian formalism to describe the system's motion.

4. How is the Lagrange multiplier method used in Euler-Lagrange for constrained system?

In Euler-Lagrange for constrained system, the Lagrange multipliers are introduced to incorporate the constraints into the Lagrangian. This allows for the use of the standard Euler-Lagrange equations to derive the equations of motion for the system with constraints.

5. What are some applications of Euler-Lagrange for constrained system?

Euler-Lagrange for constrained system has applications in various fields such as mechanics, physics, and engineering. It is used to study the motion of constrained systems such as pendulums, rigid bodies, and systems with constraints on the motion of particles. It is also used in optimization problems and in the study of constrained optimization in economics.

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