Is there a mistake in my calculation or in my reasoning?

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Homework Help Overview

The discussion revolves around solving a second-order linear differential equation with a piecewise input function using convolution. The original poster presents their attempts to compute the convolution of two functions derived from the equation and questions the validity of their results, particularly regarding the integration boundaries.

Discussion Character

  • Exploratory, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • The original poster attempts to solve the equation by breaking it into cases based on the piecewise nature of the input function. They express confusion about the results of the convolution operation and the integration limits used.

Discussion Status

Participants are actively engaging with the original poster's reasoning, suggesting a review of integration boundaries and the implications of the Heaviside functions. There is a recognition of the complexity involved in the convolution process, with some participants offering alternative perspectives on the use of Laplace transforms.

Contextual Notes

The problem involves specific initial conditions and a piecewise function that complicates the convolution process. The original poster's calculations are constrained by the nature of the input function and the assumptions made about the integration limits.

Jonas E
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Homework Statement


y'' + 3y' + 2y = r(t),

r(t) = u(t - 1) - u(t - 2),

y(0) = y'(0) = 0.

I need to solve this by convolution, which I know is commutative. The problem is that my calculation gives (f * g) =/= (g * f). Could someone please tell me where my mistake is?


Homework Equations



(f * g) = ∫f(τ)g(t-τ)dτ, from 0 to t

The Attempt at a Solution


I split the problem into 3 cases:

First (0 < t < 1): r(t) = 0, so y(t) = 0

Second (1 < t < 2): r(t) = 1 This is where it goes wrong.

I get f(t) = 1, g(t) = e^(-t) - e^(-2t), then y = (f * g) = ∫[ e^-(t-τ) - e^-2(t-τ) ]dτ, from 1 to t = (1/2) - e^-(t-1) - (1/2)e^-2(t-1), which is the correct answer according to my textbook.

But, y = (g * f) = ∫[ e^(-τ) - e^(-2τ) ]dτ, from 1 to t = -e^(-t) + (1/2)e^(-2t) + e^(-1) - (1/2)e^(-2) =/= (f * g)

I integrated from 1 instead of 0 since r=0 for t < 1.
 
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I suggest you look over your integration boundaries for the second case. Think about what the convolution really means.
 
Orodruin said:
I suggest you look over your integration boundaries for the second case. Think about what the convolution really means.
I don't think I understand. I get the right answer for (g * f) if I integrate from 0 to (t - 1) instead, but I don't understand why. Could you please explain?
 
Try writing the integrals using the actual expressions for the functions instead. Where are the heaviside functions non-zero?
 
Orodruin said:
Try writing the integrals using the actual expressions for the functions instead. Where are the heaviside functions non-zero?
I have now tried that for both (f * g) and (g * f), but in both cases I get the correct answer for case 3 (t > 2), when I'm trying to solve for case 2:

(f * g) = ∫[ e^(-τ) - e^(-2τ) ] * [ u(t - τ - 1) - u(t - τ - 2)]dτ

I find that for case 2:

t - τ - 1 > 0 Λ t - τ - 2 < 0

which gives me:

t - 2 < τ < t - 1

So the integral becomes:

[ -e^(-τ) + (1/2)e^(-2τ) ] from (t - 2) to (t - 1) = e^-(t - 2) - (1/2)e^-2(t - 2) - (e^-(t - 1) - (1/2)e^-2(t - 2))

but this is correct only if t > 2, so I don't understand why I get that when I try to solve for 1 < t < 2
 
Jonas E said:
I have now tried that for both (f * g) and (g * f), but in both cases I get the correct answer for case 3 (t > 2), when I'm trying to solve for case 2:

(f * g) = ∫[ e^(-τ) - e^(-2τ) ] * [ u(t - τ - 1) - u(t - τ - 2)]dτ

I find that for case 2:

t - τ - 1 > 0 Λ t - τ - 2 < 0

which gives me:

t - 2 < τ < t - 1

So the integral becomes:

[ -e^(-τ) + (1/2)e^(-2τ) ] from (t - 2) to (t - 1) = e^-(t - 2) - (1/2)e^-2(t - 2) - (e^-(t - 1) - (1/2)e^-2(t - 2))

but this is correct only if t > 2, so I don't understand why I get that when I try to solve for 1 < t < 2

I don't see why you want to use convolutions, instead of just applying standard properties of Laplace transforms to get an easily-recognized form of inverse Laplace transform. However, if you insist on using convolutions you will have
y(t) = \int_0^t f(t - \tau) r(\tau) \, d \tau = \underbrace{\int_0^t f(t-\tau) u(\tau-1) \, d\tau}_{= I_1} -<br /> \underbrace{\int_0^t f(t-\tau) u(\tau-2) \, d\tau}_{= I_2}
For ##t \leq 1## we have ##I_1 = 0## because the ##u##-factor vanishes. For ##t > 1## we have ##I_1 = \int_1^t f(t-\tau) \, d \tau##, etc. The term ##I_2## is similar.
 

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