## Q8.2.1

1. Use the table of Laplace transforms to find the inverse Laplace transform.

- ( {3over(s-7)^4})
- ( {2s-4over s^2-4s+13})
- ( {1over s^2+4s+20})
- ( {2over s^2+9})
- ( {s^2-1over(s^2+1)^2})
- ( {1over(s-2)^2-4})
- ( {12s-24over(s^2-4s+85)^2})
- ( {2over(s-3)^2-9})
- ( {s^2-4s+3over(s^2-4s+5)^2})

2. Use Theorem 8.2.1 and the table of Laplace transforms to find the inverse Laplace transform.

- ( {2s+3over(s-7)^4})
- ( {s^2-1over(s-2)^6})
- ( {s+5over s^2+6s+18})
- ( {2s+1over s^2+9})
- ( {sover s^2+2s+1})
- ( {s+1over s^2-9})
- ( {s^3+2s^2-s-3over(s+1)^4})
- ( {2s+3over(s-1)^2+4})
- ( {1over s}-{sover s^2+1})
- ( {3s+4over s^2-1})
- ( {3over s-1}+{4s+1over s^2+9})
- ( {3over(s+2)^2}-{2s+6over s^2+4})

3. Use Heaviside’s method to find the inverse Laplace transform.

- ( {3-(s+1)(s-2)over(s+1)(s+2)(s-2)})
- ( {7+(s+4)(18-3s)over(s-3)(s-1)(s+4)})
- ( {2+(s-2)(3-2s)over(s-2)(s+2)(s-3)})
- ( {3-(s-1)(s+1)over(s+4)(s-2)(s-1)})
- ( {3+(s-2)(10-2s-s^2)over(s-2)(s+2)(s-1)(s+3)})
- ( {3+(s-3)(2s^2+s-21)over(s-3)(s-1)(s+4)(s-2)})

4. Find the inverse Laplace transform.

- ( {2+3sover(s^2+1)(s+2)(s+1)})
- ( {3s^2+2s+1over(s^2+1)(s^2+2s+2)})
- ( {3s+2over(s-2)(s^2+2s+5)})
- ( {3s^2+2s+1over(s-1)^2(s+2)(s+3)})
- ( {2s^2+s+3over(s-1)^2(s+2)^2})
- ( {3s+2over(s^2+1)(s-1)^2})

5. Use the method of Example 8.2.9 to find the inverse Laplace transform.

- ( {3s+2over(s^2+4)(s^2+9)})
- ( {-4s+1over(s^2+1)(s^2+16)})
- ( {5s+3over(s^2+1)(s^2+4)})
- ( {-s+1over(4s^2+1)(s^2+1)})
- ( {17s-34over(s^2+16)(16s^2+1)})
- ( {2s-1over(4s^2+1)(9s^2+1)})

6. Find the inverse Laplace transform.

- ( {17 s-15over(s^2-2s+5)(s^2+2s+10)})
- ( {8s+56over(s^2-6s+13)(s^2+2s+5)})
- ( {s+9over(s^2+4s+5)(s^2-4s+13)})
- ( {3s-2over(s^2-4s+5)(s^2-6s+13)})
- ( {3s-1over(s^2-2s+2)(s^2+2s+5)})
- ( {20s+40over(4s^2-4s+5)(4s^2+4s+5)})

7. Find the inverse Laplace transform.

- ( {1over s(s^2+1)})
- ( {1over(s-1)(s^2-2s+17)})
- ( {3s+2over(s-2)(s^2+2s+10)})
- ( {34-17sover(2s-1)(s^2-2s+5)})
- ( {s+2over(s-3)(s^2+2s+5)})
- ( {2s-2over(s-2)(s^2+2s+10)})

8. Find the inverse Laplace transform.

- ( {2s+1over(s^2+1)(s-1)(s-3)})
- ( {s+2over(s^2+2s+2)(s^2-1)})
- ( {2s-1over(s^2-2s+2)(s+1)(s-2)})
- ( {s-6over(s^2-1)(s^2+4)})
- ( {2s-3over s(s-2)(s^2-2s+5)})
- ( {5s-15over(s^2-4s+13)(s-2)(s-1)})

9. Given that (f(t)leftrightarrow F(s)), find the inverse Laplace transform of (F(as-b)), where (a>0).

10.

- If (s_1), (s_2), …, (s_n) are distinct and (P) is a polynomial of degree less than (n), then [{P(s)over(s-s_1)(s-s_2)cdots(s-s_n)}= {A_1over s-s_1}+{A_2over s-s_2}+cdots+{A_nover s-s_n}. onumber ] Multiply through by (s-s_i) to show that (A_i) can be obtained by ignoring the factor (s-s_i) on the left and setting (s=s_i) elsewhere.
- Suppose (P) and (Q_1) are polynomials such that (mbox{degree}(P)lembox{degree}(Q_1)) and (Q_1(s_1) e0). Show that the coefficient of (1/(s-s_1)) in the partial fraction expansion of [F(s)={P(s)over(s-s_1)Q_1(s)} onumber ] is (P(s_1)/Q_1(s_1)).
- Explain how the results of (a) and (b) are related.

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## Computation of the inverse Laplace transform based on a collocation method which uses only real values

We develop a numerical algorithm for inverting a Laplace transform (LT), based on Laguerre polynomial series expansion of the inverse function under the assumption that the LT is known on the real axis only. The method belongs to the class of Collocation methods (C-methods), and is applicable when the LT function is regular at infinity. Difficulties associated with these problems are due to their intrinsic ill-posedness. The main contribution of this paper is to provide computable estimates of truncation, discretization, conditioning and roundoff errors introduced by numerical computations. Moreover, we introduce the pseudoaccuracy which will be used by the numerical algorithm in order to provide uniform scaled accuracy of the computed approximation for any *x* with respect to e σ x . These estimates are then employed to dynamically truncate the series expansion. In other words, the number of the terms of the series acts like the regularization parameter which provides the trade-off between errors.

With the aim to validate the reliability and usability of the algorithm experiments were carried out on several test functions.

## Solving convolution problem with $delta(x)$ function

Suppose we had the functions: $g(t)= heta(t)(e^<-t>+2e^<-2t>)+2delta(t)$ and $u(t)=2( heta(t)- heta(t-2))$ Then we have $u*g=int_<-infty>^

However, using Laplace transform I arrived to this result: $u*g=( heta(t)- heta(t-2))(16-4e^<-t>-4e^<-2t>)$

The fact that the results do not agree leads me to believe that I am missing something very important while doing the integration part.

In all of the above lines, $ heta(x)$ represents the unit step function, and $delta(x)$ is the Dirac impulse function. Using the advice I got in the comments I got : $u*g=2int_

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## Notes on Diffy Qs: Differential Equations for Engineers

Let us see how the Laplace transform is used for differential equations. First let us try to find the Laplace transform of a function that is a derivative. Suppose (g(t)) is a differentiable function of exponential order, that is, (lvert g(t)
vert leq M e^

We repeat this procedure for higher derivatives. The results are listed in Table 7.2.1. The procedure also works for piecewise smooth functions, that is functions that are piecewise continuous with a piecewise continuous derivative.

Table 7.2.1 . Laplace transforms of derivatives ((G(s) = mathcal

(f(t)) | (mathcal |

(g'(t)) | (sG(s)-g(0)) |

(g''(t)) | (s^2G(s)-sg(0)-g'(0)) |

(g'''(t)) | (s^3G(s)-s^2g(0)-sg'(0)-g''(0)) |

###### Exercise 6.2.1 .

### Subsection 6.2.2 Solving ODEs with the Laplace transform

Notice that the Laplace transform turns differentiation into multiplication by (s ext<.>) Let us see how to apply this fact to differential equations.

###### Example 6.2.1 .

We will take the Laplace transform of both sides. By (X(s)) we will, as usual, denote the Laplace transform of (x(t) ext<.>)

We plug in the initial conditions now—this makes the computations more streamlined—to obtain

We use partial fractions (exercise) to write

Now take the inverse Laplace transform to obtain

The procedure for linear constant coefficient equations is as follows. We take an ordinary differential equation in the time variable (t ext<.>) We apply the Laplace transform to transform the equation into an algebraic (non differential) equation in the frequency domain. All the (x(t) ext<,>) (x'(t) ext<,>) (x''(t) ext<,>) and so on, will be converted to (X(s) ext<,>) (sX(s) - x(0) ext<,>) (s^2X(s) - sx(0) - x'(0) ext<,>) and so on. We solve the equation for (X(s) ext<.>) Then taking the inverse transform, if possible, we find (x(t) ext<.>)

It should be noted that since not every function has a Laplace transform, not every equation can be solved in this manner. Also if the equation is not a linear constant coefficient ODE, then by applying the Laplace transform we may not obtain an algebraic equation.

### Subsection 6.2.3 Using the Heaviside function

Before we move on to more general equations than those we could solve before, we want to consider the Heaviside function. See Figure 6.1 for the graph.

This function is useful for putting together functions, or cutting functions off. Most commonly it is used as (u(t-a)) for some constant (a ext<.>) This just shifts the graph to the right by (a ext<.>) That is, it is a function that is 0 when (t < a) and 1 when (t geq a ext<.>) Suppose for example that (f(t)) is a “signal” and you started receiving the signal (sin t) at time (t=pi ext<.>) The function (f(t)) should then be defined as

Using the Heaviside function, (f(t)) can be written as

Similarly the step function that is 1 on the interval ([1,2)) and zero everywhere else can be written as

The Heaviside function is useful to define functions defined piecewise. If you want to define (f(t)) such that (f(t) = t) when (t) is in ([0,1] ext<,>) (f(t) = -t+2) when (t) is in ([1,2] ext<,>) and (f(t) = 0) otherwise, then you can use the expression

Hence it is useful to know how the Heaviside function interacts with the Laplace transform. We have already seen that

This can be generalized into a *shifting property* or *second shifting property*.

###### Example 6.2.2 .

Suppose that the forcing function is not periodic. For example, suppose that we had a mass-spring system

where (f(t) = 1) if (1 leq t < 5) and zero otherwise. We could imagine a mass-spring system, where a rocket is fired for 4 seconds starting at (t=1 ext<.>) Or perhaps an RLC circuit, where the voltage is raised at a constant rate for 4 seconds starting at (t=1 ext<,>) and then held steady again starting at (t=5 ext<.>)

We can write (f(t) = u(t-1) - u(t-5) ext<.>) We transform the equation and we plug in the initial conditions as before to obtain

We solve for (X(s)) to obtain

We leave it as an exercise to the reader to show that

In other words (mathcal ~~ ext<.>) So using (6.1) we find~~

The plot of this solution is given in Figure 6.2.

Figure 6.2 . Plot of (x(t) ext<.>)

### Subsection 6.2.4 Transfer functions

The Laplace transform leads to the following useful concept for studying the steady state behavior of a linear system. Consider an equation of the form

where (L) is a linear constant coefficient differential operator. Then (f(t)) is usually thought of as input of the system and (x(t)) is thought of as the output of the system. For example, for a mass-spring system the input is the forcing function and the output is the behavior of the mass. We would like to have a convenient way to study the behavior of the system for different inputs.

Let us suppose that all the initial conditions are zero and take the Laplace transform of the equation, we obtain the equation

Solving for the ratio (
icefrac*transfer function* (H(s) =
icefrac<1> ext<,>) that is,

In other words, (X(s) = H(s) F(s) ext<.>) We obtain an algebraic dependence of the output of the system based on the input. We can now easily study the steady state behavior of the system given different inputs by simply multiplying by the transfer function.

###### Example 6.2.3 .

Given (x'' + omega_0^2 x = f(t) ext<,>) let us find the transfer function (assuming the initial conditions are zero).

First, we take the Laplace transform of the equation.

Now we solve for the transfer function (
icefrac

Let us see how to use the transfer function. Suppose we have the constant input (f(t) = 1 ext<.>) Hence (F(s) =
icefrac<1>~~ ext<,>) and~~

~~ ~~

~~Taking the inverse Laplace transform of (X(s)) we obtain~~

### Subsection 6.2.5 Transforms of integrals

A feature of Laplace transforms is that it is also able to easily deal with integral equations. That is, equations in which integrals rather than derivatives of functions appear. The basic property, which can be proved by applying the definition and doing integration by parts, is

It is sometimes useful (e.g. for computing the inverse transform) to write this as

###### Example 6.2.4 .

To compute (~~
ight>) we could proceed by applying this integration rule.~~

###### Example 6.2.5 .

An equation containing an integral of the unknown function is called an *integral equation*. For example, take

where we wish to solve for (x(t) ext<.>) We apply the Laplace transform and the shifting property to get

where (X(s) = mathcal

We use the shifting property again

### Subsection 6.2.6 Exercises

###### Exercise 6.2.2 .

Using the Heaviside function write down the piecewise function that is 0 for (t < 0 ext<,>) (t^2) for (t) in ([0,1]) and (t) for (t > 1 ext<.>)

###### Exercise 6.2.3 .

Using the Laplace transform solve

where (m > 0 ext<,>) (c > 0 ext<,>) (k > 0 ext<,>) and (c^2 - 4km > 0) (system is overdamped).

###### Exercise 6.2.4 .

Using the Laplace transform solve

where (m > 0 ext<,>) (c > 0 ext<,>) (k > 0 ext<,>) and (c^2 - 4km < 0) (system is underdamped).

###### Exercise 6.2.5 .

Using the Laplace transform solve

where (m > 0 ext<,>) (c > 0 ext<,>) (k > 0 ext<,>) and (c^2 = 4km) (system is critically damped).

###### Exercise 6.2.6 .

Solve (x'' + x = u(t-1)) for initial conditions (x(0) = 0) and (x'(0) = 0 ext<.>)

###### Exercise 6.2.7 .

Show the differentiation of the transform property. Suppose (mathcal

Hint: Differentiate under the integral sign.

###### Exercise 6.2.8 .

Solve (x''' + x = t^3 u(t-1)) for initial conditions (x(0) = 1) and (x'(0) = 0 ext<,>) (x''(0) = 0 ext<.>)

###### Exercise 6.2.9 .

Show the second shifting property: (mathcal

###### Exercise 6.2.10 .

Let us think of the mass-spring system with a rocket from Example 6.2.2. We noticed that the solution kept oscillating after the rocket stopped running. The amplitude of the oscillation depends on the time that the rocket was fired (for 4 seconds in the example).

Find a formula for the amplitude of the resulting oscillation in terms of the amount of time the rocket is fired.

Is there a nonzero time (if so what is it?) for which the rocket fires and the resulting oscillation has amplitude 0 (the mass is not moving)?

###### Exercise 6.2.11 .

Sketch the graph of (f(t) ext<.>)

Write down (f(t)) using the Heaviside function.

Solve (x''+x=f(t) ext<,>) (x(0)=0 ext<,>) (x'(0) = 0) using Laplace transform.

###### Exercise 6.2.12 .

Find the transfer function for (m x'' + c x' + kx = f(t)) (assuming the initial conditions are zero).

###### Exercise 6.2.101 .

Using the Heaviside function (u(t) ext<,>) write down the function

(f(t) = (t-1)igl(u(t-1) - u(t-2)igr) + u(t-2))

###### Exercise 6.2.102 .

Solve (x''-x = (t^2-1) u(t-1)) for initial conditions (x(0)=1 ext<,>) (x'(0) = 2) using the Laplace transform.

###### Exercise 6.2.103 .

Find the transfer function for (x' + x = f(t)) (assuming the initial conditions are zero).

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