Solve the integro-differential equation \[\int\limits_0^xy(u)\,\mathrm du-y'(x)=x\]
i've got this,
but the answer in the back of the book says \[=y_0\cosh x-\cosh x+1\\ = (y_0-1)\cosh x+1\]
@zzr0ck3r googles integro-differential to see if it is taken for a band name. NOPE!
Maybe this is the problem, but I don't think it should matter so I'll keep looking. \[Y=(y_0-X)\frac{p}{p^2-1} = y_0 \frac{p}{p^2-1} +\frac{1}{1-p^2}\]
Oh nevermind, I think my correction is wrong, I was thinking \(X=\frac{1}{p}\) but really it's \(\frac{1}{p^2}\) isn't it. I guess that's lame, and I suppose you're doing the convolution to avoid partial fractions so I don't blame you.
All of your work looks completely correct to me. Maybe it can be rearranged from one into the other ugh lol.
sinh = cosh ?
Or your book is wrong. We can try checking to see if the answers satisfy the integro-differential equation.
The book answer is right, your answer is wrong in general but true with \(y_0=0\) so that might give some clues.
By a different method im getting y(x) = C*coshx + 1
hmmm
I am not sure but I don't think the inverse laplace transform was done correctly here: \[\mathcal{L}^{-1}\{y_0-X\} = y_0-x\]
I'll need to review laplace transofrms to understand your method, but your y(x) is clearly wrong as it doesn't satisfy the given equation
what is the inverse Laplace of a constant?
Dirac delta? Not sure
oh, yeah the delta thingo
seems like that could plausibly fix it, not gonna work it out though unless you say it doesn't work haha
how could partial fractions be used instead?
Well if you expand X and avoid the convolution, then you end up with: \[\frac{1}{p^2} \frac{p}{p^2-1} = \frac{1}{p(p^2-1)} = -\frac{1}{p}+\frac{1}{2} \frac{1}{p+1}+\frac{1}{2} \frac{1}{p-1} \] then just transform these terms individually.
Looks like these will inverse transform into some exponentials, which is fine cause we can make cosh and sinh out of exponentials.
What method did you use @ganeshie8 ?
Differentiate through out, solve the second order ode, then reduce the constants...
The solutions of \[\int\limits_0^xy(u)\,\mathrm du-y'(x)=x\tag{1}\] are a subset of the solutions to \[y - y'' = 1\tag{2}\] Not hard to see that \(y = 1\) is a particular solution to \((2)\) The null solution is \(c_1e^x + c_2e^{-x}\). The complete solution to \((2)\) is \(y = 1+c_1e^x + c_2e^{-x}\) Plugging this in \((1)\) gives \(c_1=c_2\), so the general solution to \((1)\) has to be \(y = c(e^x + e^{-x})+1\), which can be rearranged as \(y = C* \cosh x + 1\)
I can now get your method to work @ganeshie8 , it's not hard to solve 2nd order DE. Thank you for providing it. However I would still like to fix my Laplace convolution method
I think you are right about my error @Kainui \[\mathcal{L}^{-1}\{y_0-X\} \neq y_0-x\] but i'm not really sure how to fix this
Alright I'll pick it up right where you left it off and give you some stuff to finish it on your own I think cause it should boil down to just distributing mostly the same work you have already done. \[Y= (y_0-X)\frac{p}{p^2-1}\]\[y=\mathcal{L}^{-1}[\mathcal{L}\{y_0\delta(x) -x\}\mathcal{L}\{\cosh(x)\}] = (y_0 \delta(x)-x) \star \cosh(x) \] Actually, if you don't know how to derive the convolution, I think it's definitely worth your time cause it's pretty ubiquitous, it's a way of sidestepping multiplying two series together and looking at only their coefficients and is sorta a meeting point of linear algebra and group theory. Ok so on with the calculation... \[y =\int_0^x [y_0 \delta(x-u) - (x-u)] \cosh(u)du\] One of these integrals you have already solved so I'll just give you what you need: \[\int_0^x \delta(x-u) f(u)du = f(x)\] You can think of \(\delta(0)=\infty\) and all other values \(\delta(t)=0\). It's essentially the identity matrix, and is the identity element of the group of functions with the convolution as the binary operation of this abelian group... Too much information, w/e throw it away lol. That should be enough to solve it now: \[y =y_0 \cosh(x)+\int_0^x - (x-u) \cosh(u)du\]
Yeah continuing this on, I am getting the exact answer as your book now. Awesome.
Just to sorta show the forward way, since x=0 is the only value that \(\delta(x)\) is nonzero, it "pulls out" that value: \[\mathcal{L}\{\delta\}(p)=\int_0^\infty \delta(x) e^{-px} dx = e^{-p0}= 1\]
\[\boxed{ \newcommand \dd [1] {\,\mathrm d#1} % infinitesimal \newcommand \intl[4] {\int\limits_{#1}^{#2}{#3}{\dd #4}} % integral_a^b{f(x)}dx \newcommand \Lap [1] {\operatorname{\mathcal L}\left\{#1\right\}} % Laplace transform (p) \newcommand \Lin [1] {\operatorname{\mathcal L}^{-1}\left\{#1\right\}} % inverse Laplace transform \newcommand \Ev [3] {\left.{#1}\right|_{#2}^{#3}} % evaluation limits \newcommand \ps [1] {\left(#1\right)} % dynamic parentheses }\] \[ \begin{align} \intl0x{y(u)}u-y'(x) &= x\\ \Lap{1\star y}-\Lap{y'} &= X\\ \frac1p\cdot Y - \ps{pY-y_0} &=\\ \ps{\frac1p-p}Y &= X-y_0\\ Y &= \ps{X-y_0}{\frac1{\frac1p-p}}\\ &= \ps{y_0-X}{\frac p{p^2-1}}\\ y(x)&= \ps{y_0\delta(x)-x}\star\cosh x\\ &= \intl0x{(y_0\delta(x-u)-(x-u))\cosh u}u\\ &= y_0\intl0x{\delta(x-u)\cosh u}u-x\intl0x{\cosh u}u + \intl0x{u\cosh u}u\\ &= y_0\Ev{\cosh u}{}x-x\Ev{\sinh u}0x + \Ev{u\sinh u}0x-\intl0x{\sinh u}u\\ &= y_0\cosh x-x\sinh x + x\sinh x-\Ev{\cosh u}0x\\ &= y_0\cosh x - \cosh x + 1\\ &= \ps{y_0-1}\cosh x+1 \end{align} \]
We have \[y(x) = (y_0-1)\cosh x+1\] Taking the derivative \[y'(x)=(y_0-1)\sinh x\] and integral: \[\intl0x{y(u)}u= (y_0-1)\intl0x{\cosh u+1}u\\ \qquad\qquad = (y_0-1)\sinh x+x\] Plugging these into the IDE \[\int\limits_0^xy(u)\,\mathrm du-y'(x)=x\\ \]\[LHS = \Big[(y_0-1)\sinh x+x\Big]-\Big[ (y_0-1)\sinh x\Big] \\ \qquad = x\\ \qquad = RHS\]
vanilla way, starting at second line \(\dfrac{1}{p} Y - p Y + y_o = \dfrac{1}{p^2}\) \(Y = \dfrac{p}{p^2 -1^2} y_o - \dfrac{1}{p} \dfrac{1}{p^2 - 1^2}\) \( = \mathcal{L} \{ y_o \cosh x\} - \mathcal{L} \{1\} \mathcal{L} \{\sinh x\}\) Second bit is convolution \(y = y_o \cosh x - \int\limits_0^x \sinh \tau d \tau\) \(y = y_o \cosh x - \left. \cosh \tau \right|_0^x\)
That's much better. @IrishBoy123
Join our real-time social learning platform and learn together with your friends!