Kamis, 05 Mei 2011

Transformasi Lapace 2

History

The Laplace transform is named in honor of mathematician and astronomer Pierre-Simon Laplace, who used the transform in his work on probability theory. From 1744, Leonhard Euler investigated integrals of the form

as solutions of differential equations but did not pursue the matter very far.[2] Joseph Louis Lagrange was an admirer of Euler and, in his work on integrating probability density functions, investigated expressions of the form

which some modern historians have interpreted within modern Laplace transform theory.[3][4][clarification needed]
These types of integrals seem first to have attracted Laplace's attention in 1782 where he was following in the spirit of Euler in using the integrals themselves as solutions of equations.[5] However, in 1785, Laplace took the critical step forward when, rather than just looking for a solution in the form of an integral, he started to apply the transforms in the sense that was later to become popular. He used an integral of the form:

akin to a Mellin transform, to transform the whole of a difference equation, in order to look for solutions of the transformed equation. He then went on to apply the Laplace transform in the same way and started to derive some of its properties, beginning to appreciate its potential power.[6]
Laplace also recognised that Joseph Fourier's method of Fourier series for solving the diffusion equation could only apply to a limited region of space as the solutions were periodic. In 1809, Laplace applied his transform to find solutions that diffused indefinitely in space.[7]
[edit]Formal definition

The Laplace transform of a function f(t), defined for all real numbers t ≥ 0, is the function F(s), defined by:

The parameter s is a complex number:
with real numbers σ and ω.
The meaning of the integral depends on types of functions of interest. A necessary condition for existence of the integral is that ƒ must be locally integrable on [0,∞). For locally integrable functions that decay at infinity or are of exponential type, the integral can be understood as a (proper) Lebesgue integral. However, for many applications it is necessary to regard it as a conditionally convergent improper integral at ∞. Still more generally, the integral can be understood in a weak sense, and this is dealt with below.
One can define the Laplace transform of a finite Borel measure μ by the Lebesgue integral[8]

An important special case is where μ is a probability measure or, even more specifically, the Dirac delta function. In operational calculus, the Laplace transform of a measure is often treated as though the measure came from a distribution function ƒ. In that case, to avoid potential confusion, one often writes

where the lower limit of 0− is short notation to mean

This limit emphasizes that any point mass located at 0 is entirely captured by the Laplace transform. Although with the Lebesgue integral, it is not necessary to take such a limit, it does appear more naturally in connection with the Laplace–Stieltjes transform.
[edit]Probability theory
In pure and applied probability, the Laplace transform is defined by means of an expectation value. If X is a random variable with probability density function ƒ, then the Laplace transform of ƒ is given by the expectation

By abuse of language, this is referred to as the Laplace transform of the random variable X itself. Replacing s by −t gives the moment generating function of X. The Laplace transform has applications throughout probability theory, including first passage times of stochastic processes such as Markov chains, and renewal theory.
[edit]Bilateral Laplace transform
Main article: Two-sided Laplace transform
When one says "the Laplace transform" without qualification, the unilateral or one-sided transform is normally intended. The Laplace transform can be alternatively defined as the bilateral Laplace transform or two-sided Laplace transform by extending the limits of integration to be the entire real axis. If that is done the common unilateral transform simply becomes a special case of the bilateral transform where the definition of the function being transformed is multiplied by the Heaviside step function.
The bilateral Laplace transform is defined as follows:

[edit]Inverse Laplace transform
For more details on this topic, see Inverse Laplace transform.
The inverse Laplace transform is given by the following complex integral, which is known by various names (the Bromwich integral, the Fourier-Mellin integral, and Mellin's inverse formula):

where γ is a real number so that the contour path of integration is in the region of convergence of F(s). An alternative formula for the inverse Laplace transform is given by Post's inversion formula.
[edit]Region of convergence

If ƒ is a locally integrable function (or more generally a Borel measure locally of bounded variation), then the Laplace transform F(s) of ƒ converges provided that the limit

exists. The Laplace transform converges absolutely if the integral

exists (as proper Lebesgue integral). The Laplace transform is usually understood as conditionally convergent, meaning that it converges in the former instead of the latter sense.
The set of values for which F(s) converges absolutely is either of the form Re{s} > a or else Re{s} ≥ a, where a is an extended real constant, −∞ ≤ a ≤ ∞. (This follows from the dominated convergence theorem.) The constant a is known as the abscissa of absolute convergence, and depends on the growth behavior of ƒ(t).[9] Analogously, the two-sided transform converges absolutely in a strip of the form a < Re{s} < b, and possibly including the lines Re{s} = a or Re{s} = b.[10] The subset of values of s for which the Laplace transform converges absolutely is called the region of absolute convergence or the domain of absolute convergence. In the two-sided case, it is sometimes called the strip of absolute convergence. The Laplace transform is analytic in the region of absolute convergence.
Similarly, the set of values for which F(s) converges (conditionally or absolutely) is known as the region of conditional convergence, or simply the region of convergence (ROC). If the Laplace transform converges (conditionally) at s = s0, then it automatically converges for all s with Re{s} > Re{s0}. Therefore the region of convergence is a half-plane of the form Re{s} > a, possibly including some points of the boundary line Re{s} = a. In the region of convergence Re{s} > Re{s0}, the Laplace transform of ƒ can be expressed by integrating by parts as the integral

That is, in the region of convergence F(s) can effectively be expressed as the absolutely convergent Laplace transform of some other function. In particular, it is analytic.
A variety of theorems, in the form of Paley–Wiener theorems, exist concerning the relationship between the decay properties of ƒ and the properties of the Laplace transform within the region of convergence.
In engineering applications, a function corresponding to a linear time-invariant (LTI) system is stable if every bounded input produces a bounded output. This is equivalent to the absolute convergence of the Laplace transform of the impulse response function in the region Re{s} ≥ 0. As a result, LTI systems are stable provided the poles of the Laplace transform of the impulse response function have negative real part.
[edit]Properties and theorems

The Laplace transform has a number of properties that make it useful for analyzing linear dynamical systems. The most significant advantage is that differentiation and integration become multiplication and division, respectively, by s (similarly to logarithms changing multiplication of numbers to addition of their logarithms). Because of this property, the Laplace variable s is also known as operator variable in the L domain: either derivative operator or (for s−1) integration operator. The transform turns integral equations and differential equations to polynomial equations, which are much easier to solve. Once solved, use of the inverse Laplace transform reverts back to the time domain.
Given the functions f(t) and g(t), and their respective Laplace transforms F(s) and G(s):


the following table is a list of properties of unilateral Laplace transform:[11]
Properties of the unilateral Laplace transform
Time domain 's' domain Comment
Linearity Can be proved using basic rules of integration.
Frequency differentiation is the first derivative of .
Frequency differentiation More general form, nth derivative of F(s).
Differentiation ƒ is assumed to be a differentiable function, and its derivative is assumed to be of exponential type. This can then be obtained by integration by parts
Second Differentiation ƒ is assumed twice differentiable and the second derivative to be of exponential type. Follows by applying the Differentiation property to .
General Differentiation ƒ is assumed to be n-times differentiable, with nth derivative of exponential type. Follow by mathematical induction.
Frequency integration
Integration u(t) is the Heaviside step function. Note (u * f)(t) is the convolution of u(t) and f(t).
Scaling where a is positive.
Frequency shifting
Time shifting u(t) is the Heaviside step function
Multiplication the integration is done along the vertical line Re(σ) = c that lies entirely within the region of convergence of F.[12]
Convolution ƒ(t) and g(t) are extended by zero for t < 0 in the definition of the convolution.
Periodic Function f(t) is a periodic function of period T so that . This is the result of the time shifting property and the geometric series.
Initial value theorem:

Final value theorem:
, if all poles of sF(s) are in the left half-plane.
The final value theorem is useful because it gives the long-term behaviour without having to perform partial fraction decompositions or other difficult algebra. If a function's poles are in the right-hand plane (e.g. et or sin(t)) the behaviour of this formula is undefined.
[edit]Proof of the Laplace transform of a function's derivative
It is often convenient to use the differentiation property of the Laplace transform to find the transform of a function's derivative. This can be derived from the basic expression for a Laplace transform as follows:

yielding

and in the bilateral case,

The general result

where fn is the n-th derivative of f, can then be established with an inductive argument.
[edit]Evaluating improper integrals
Let , then (see the table above)

or

Let we get the identity

For example,

Another example is Dirichlet integral.
[edit]Relationship to other transforms
[edit]Laplace–Stieltjes transform
The (unilateral) Laplace–Stieltjes transform of a function g : R → R is defined by the Lebesgue–Stieltjes integral

The function g is assumed to be of bounded variation. If g is the antiderivative of ƒ:

then the Laplace–Stieltjes transform of g and the Laplace transform of ƒ coincide. In general, the Laplace–Stieltjes transform is the Laplace transform of the Stieltjes measure associated to g. So in practice, the only distinction between the two transforms is that the Laplace transform is thought of as operating on the density function of the measure, whereas the Laplace–Stieltjes transform is thought of as operating on its cumulative distribution function.[13]
[edit]Fourier transform
The continuous Fourier transform is equivalent to evaluating the bilateral Laplace transform with imaginary argument s = iω or s = 2πfi :

This expression excludes the scaling factor , which is often included in definitions of the Fourier transform. This relationship between the Laplace and Fourier transforms is often used to determine the frequency spectrum of a signal or dynamical system.
The above relation is valid as stated if and only if the region of convergence (ROC) of F(s) contains the imaginary axis, σ = 0. For example, the function f(t) = cos(ω0t)u(t) has a Laplace transform F(s) = s/(s2 + ω02) whose ROC is Re(s) > 0. Therefore, substituting s = iω in F(s) does not yield the Fourier transform of f(t) = cos(ω0t).
However, a relation of the form

holds under much weaker conditions. For instance, this holds for the above example provided that the limit is understood as a weak limit of measures (see vague topology). General conditions relating the limit of the Laplace transform of a function on the boundary to the Fourier transform take the form of Paley-Wiener theorems.
[edit]Mellin transform
The Mellin transform and its inverse are related to the two-sided Laplace transform by a simple change of variables. If in the Mellin transform

we set θ = e-t we get a two-sided Laplace transform.
[edit]Z-transform
The unilateral or one-sided Z-transform is simply the Laplace transform of an ideally sampled signal with the substitution of

where is the sampling period (in units of time e.g., seconds) and is the sampling rate (in samples per second or hertz)
Let

be a sampling impulse train (also called a Dirac comb) and

be the continuous-time representation of the sampled
are the discrete samples of .
The Laplace transform of the sampled signal is

This is precisely the definition of the unilateral Z-transform of the discrete function

with the substitution of .
Comparing the last two equations, we find the relationship between the unilateral Z-transform and the Laplace transform of the sampled signal:

The similarity between the Z and Laplace transforms is expanded upon in the theory of time scale calculus.
[edit]Borel transform
The integral form of the Borel transform

is a special case of the Laplace transform for ƒ an entire function of exponential type, meaning that

for some constants A and B. The generalized Borel transform allows a different weighting function to be used, rather than the exponential function, to transform functions not of exponential type. Nachbin's theorem gives necessary and sufficient conditions for the Borel transform to be well defined.
[edit]Fundamental relationships
Since an ordinary Laplace transform can be written as a special case of a two-sided transform, and since the two-sided transform can be written as the sum of two one-sided transforms, the theory of the Laplace-, Fourier-, Mellin-, and Z-transforms are at bottom the same subject. However, a different point of view and different characteristic problems are associated with each of these four major integral transforms.
[edit]Table of selected Laplace transforms

The following table provides Laplace transforms for many common functions of a single variable. For definitions and explanations, see the Explanatory Notes at the end of the table.
Because the Laplace transform is a linear operator:
The Laplace transform of a sum is the sum of Laplace transforms of each term.

The Laplace transform of a multiple of a function is that multiple times the Laplace transformation of that function.

The unilateral Laplace transform takes as input a function whose time domain is the non-negative reals, which is why all of the time domain functions in the table below are multiples of the Heaviside step function, u(t). The entries of the table that involve a time delay τ are required to be causal (meaning that τ > 0). A causal system is a system where the impulse response h(t) is zero for all time t prior to t = 0. In general, the region of convergence for causal systems is not the same as that of anticausal systems.
ID Function Time domain
Laplace s-domain
Region of convergence
1 ideal delay
1a unit impulse 1
2 delayed nth power
with frequency shift
2a nth power
( for integer n )

2a.1 qth power
( for complex q )

2a.2 unit step
2b delayed unit step
2c ramp
2d nth power with frequency shift
2d.1 exponential decay
3 exponential approach
4 sine
5 cosine
6 hyperbolic sine
7 hyperbolic cosine
8 Exponentially-decaying
sine wave
9 Exponentially-decaying
cosine wave
10 nth root
11 natural logarithm
12 Bessel function
of the first kind,
of order n

13 Modified Bessel function
of the first kind,
of order n
14 Bessel function
of the second kind,
of order 0
15 Modified Bessel function
of the second kind,
of order 0
16 Error function
Explanatory notes:
represents the Heaviside step function.
represents the Dirac delta function.
represents the Gamma function.
is the Euler–Mascheroni constant.
, a real number, typically represents time,
although it can represent any independent dimension.
is the complex angular frequency, and Re{s} is its real part.
, , , and are real numbers.
n is an integer.
[edit]s-Domain equivalent circuits and impedances

The Laplace transform is often used in circuit analysis, and simple conversions to the s-Domain of circuit elements can be made. Circuit elements can be transformed into impedances, very similar to phasor impedances.
Here is a summary of equivalents:

Note that the resistor is exactly the same in the time domain and the s-Domain. The sources are put in if there are initial conditions on the circuit elements. For example, if a capacitor has an initial voltage across it, or if the inductor has an initial current through it, the sources inserted in the s-Domain account for that.
The equivalents for current and voltage sources are simply derived from the transformations in the table above.
[edit]Examples: How to apply the properties and theorems

The Laplace transform is used frequently in engineering and physics; the output of a linear time invariant system can be calculated by convolving its unit impulse response with the input signal. Performing this calculation in Laplace space turns the convolution into a multiplication; the latter being easier to solve because of its algebraic form. For more information, see control theory.
The Laplace transform can also be used to solve differential equations and is used extensively in electrical engineering. The Laplace transform reduces a linear differential equation to an algebraic equation, which can then be solved by the formal rules of algebra. The original differential equation can then be solved by applying the inverse Laplace transform. The English electrical engineer Oliver Heaviside first proposed a similar scheme, although without using the Laplace transform; and the resulting operational calculus is credited as the Heaviside calculus.
[edit]Example 1: Solving a differential equation
In nuclear physics, the following fundamental relationship governs radioactive decay: the number of radioactive atoms N in a sample of a radioactive isotope decays at a rate proportional to N. This leads to the first order linear differential equation

where λ is the decay constant. The Laplace transform can be used to solve this equation.
Rearranging the equation to one side, we have

Next, we take the Laplace transform of both sides of the equation:

where

and

Solving, we find

Finally, we take the inverse Laplace transform to find the general solution

which is indeed the correct form for radioactive decay.
[edit]Example 2: Deriving the complex impedance for a capacitor
In the theory of electrical circuits, the current flow in a capacitor is proportional to the capacitance and rate of change in the electrical potential (in SI units). Symbolically, this is expressed by the differential equation

where C is the capacitance (in farads) of the capacitor, i = i(t) is the electric current (in amperes) through the capacitor as a function of time, and v = v(t) is the voltage (in volts) across the terminals of the capacitor, also as a function of time.
Taking the Laplace transform of this equation, we obtain

where


and

Solving for V(s) we have

The definition of the complex impedance Z (in ohms) is the ratio of the complex voltage V divided by the complex current I while holding the initial state Vo at zero:

Using this definition and the previous equation, we find:

which is the correct expression for the complex impedance of a capacitor.
[edit]Example 3: Method of partial fraction expansion
Consider a linear time-invariant system with transfer function

The impulse response is simply the inverse Laplace transform of this transfer function:

To evaluate this inverse transform, we begin by expanding H(s) using the method of partial fraction expansion:

The unknown constants P and R are the residues located at the corresponding poles of the transfer function. Each residue represents the relative contribution of that singularity to the transfer function's overall shape. By the residue theorem, the inverse Laplace transform depends only upon the poles and their residues. To find the residue P, we multiply both sides of the equation by s + α to get

Then by letting s = −α, the contribution from R vanishes and all that is left is

Similarly, the residue R is given by

Note that

and so the substitution of R and P into the expanded expression for H(s) gives

Finally, using the linearity property and the known transform for exponential decay (see Item #3 in the Table of Laplace Transforms, above), we can take the inverse Laplace transform of H(s) to obtain:

which is the impulse response of the system.
[edit]Example 4: Mixing sines, cosines, and exponentials
Time function Laplace transform

Starting with the Laplace transform

we find the inverse transform by first adding and subtracting the same constant α to the numerator:

By the shift-in-frequency property, we have

Finally, using the Laplace transforms for sine and cosine (see the table, above), we have


[edit]Example 5: Phase delay
Time function Laplace transform


Starting with the Laplace transform,

we find the inverse by first rearranging terms in the fraction:

We are now able to take the inverse Laplace transform of our terms:

This is just the sine of the sum of the arguments, yielding:
x(t) = sin(ωt + φ).
We can apply similar logic to find that

[edit]See also

Pierre-Simon Laplace
Laplace transform applied to differential equations
Moment-generating function
Z-transform (discrete equivalent of the Laplace transform)
Fourier transform
Sumudu transform or Laplace–Carson transform
Analog signal processing
Continuous-repayment mortgage
Hardy–Littlewood tauberian theorem
Bernstein's theorem
Symbolic integration

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