Laplace Transform

合集下载

拉普拉斯变换LAPLACETRANSFORM资料

拉普拉斯变换LAPLACETRANSFORM资料
证:L[ f (t)] f (t) estdt 0 令 est u du sestdt
udv uv vdu
f (t) dt dv v f (t)
积分
0
f (t) estdt uv vdu
est f (t) f (t) (sest )dt
0
0
f
(0 ) s
0
f
(t) estdt
sF (s) f (0 )
7
二、微分性质: L[ f (t)] sF(s) f (0 )
例13-3 求象函数:
(1)f (t) cost
解: d sint cost
dt
L[cost] L[ 1 d sint] 1 L[ d sint]
dt
dt
1
[s
LAPLACE TRANSFORM
1
历史的回顾
—— 小结线性电路分析
一、电阻电路的直流分析:
二、低阶动态电路的时域分析:
列、解微分方程:较难。1、列;2、解:定动态元件的初态 状态 [ uC(0+)、iL(0+) ] 和定积分常数。 优点:物理概念明确。 三、正弦稳态分析: 频域分析:相量法。
四、非正弦周期函数的谐波分析: 五、非周期函数电路的傅立叶积分:
s pn
Ki为待定之系数。
①将上式两边乘以(s-p1),先约分,后代数。
(s
p1)
F(s)
K1
(s
p1 )(
s
K2 p2
s
Kn pn
)
令s=p1,代入上式,
K1 [( s p1 ) F (s)]s p1 ②同理可得:
Ki [( s pi ) F (s)]s pi

c语言 拉氏变换

c语言 拉氏变换

c语言拉氏变换拉氏变换(Laplace Transform)是一种重要的数学工具,广泛应用于控制理论、信号处理、电路分析等领域。

它是由法国数学家皮埃尔-西蒙·拉普拉斯于18世纪末提出的,用于解决微分方程和积分方程的问题。

本文将简要介绍拉氏变换的基本概念、性质以及应用。

我们来了解一下拉氏变换的定义。

拉氏变换是一种通过对函数进行积分得到新函数的变换方法。

对于一个函数f(t),它的拉氏变换记作F(s),其中s是一个复变量。

拉氏变换的定义如下:F(s) = L{f(t)} = ∫[0,∞] e^(-st) f(t) dt其中,e^(-st)是一个指数函数,s是复平面上的一个点。

通过对函数f(t)进行积分,并乘以指数函数e^(-st),就得到了它的拉氏变换F(s)。

这个变换可以将一个函数从时域(t域)转换到复平面上的频率域(s域)。

接下来,我们来讨论一下拉氏变换的性质。

拉氏变换具有一系列重要的性质,这些性质对于分析和求解问题非常有用。

首先是线性性质。

对于任意的两个函数f(t)和g(t),以及对应的拉氏变换F(s)和G(s),拉氏变换具有线性性质,即:L{af(t) + bg(t)} = aF(s) + bG(s)其中a和b是任意常数。

这个性质使得我们可以方便地处理多个函数的变换。

其次是位移性质。

拉氏变换具有位移性质,即:L{f(t-a)} = e^(-as)F(s)这个性质表示,如果将函数f(t)在时间上向右平移a个单位,那么它的拉氏变换将在频率域上乘以一个指数函数e^(-as)。

还有频率缩放性质。

拉氏变换具有频率缩放性质,即:L{f(at)} = (1/a)F(s/a)这个性质表示,如果将函数f(t)的时间缩放为原来的a倍,那么它的拉氏变换将在频率域上缩放为原来的1/a倍。

拉氏变换还具有导数性质、积分性质以及初值定理等重要性质。

这些性质使得我们可以通过拉氏变换来求解微分方程和积分方程,简化了问题的分析和计算过程。

第四章 拉普拉斯变换

第四章 拉普拉斯变换

F ( s a)
1 s F a a

df (t ) dt
SF(s) f (0 )
F ( s ) f 1 ( 0 ) s s

t

f ( ) d
12
拉氏变换的基本性质(2) 1 s F 尺度变换 f (at) a a
初值定理
t 0
lim f ( t ) f ( 0 ) lim SF ( s )
n! s n 1 1
s2 1
e
st 0
11
5.3 拉氏变换的基本性质(1)
线性
k i f i (t )
i 1
n
k .LT [ f (t )]
i 1 i
n
时移 尺度变换
f (t t0 )u(t t0 )
e
st 0
F ( s)
f (at)
f (t )e
at
频移
微分 积分
例:衰减余弦的拉氏变换
S F0 ( S ) LT [cos t ] 2 2 S
f (t ) e
t
cost
频移特性
S F (S ) 2 2 (S )
15
例:求下式的拉氏变换
f (t )
f (t ) sin t[u(t ) u(t 1)]
f (0

)
S
lim S F ( S ) lim
S F( S )
S
1 S 1 sa
f ( )
lim
S 0
lim
S
S 0
1 0 sa
注意:f(t)=e-at u(t),
若a>0,则终值为0 若a<0,则终值不存在 如果原信号是等幅震荡或增长的, 则其终值不存在。

matlab拉氏变换

matlab拉氏变换

MATLAB拉氏变换拉氏变换(Laplace Transform)是一种常用于信号处理和控制系统分析的数学工具。

它将一个函数从时域转换到复频域,使得分析和处理连续时间系统更加方便。

MATLAB是一种强大的数值计算软件,提供了丰富的函数和工具箱,可以方便地进行拉氏变换的计算和分析。

什么是拉氏变换?拉氏变换是一种将函数从时域(时间域)转换到复频域的数学变换。

它通过将一个函数表示为复频域上的积分形式,使得原本复杂的微分方程可以转化为简单的代数方程。

拉氏变换可以用来解决线性时不变系统的微分方程,以及分析信号的频谱特性和系统的稳定性。

对于一个连续时间函数 f(t),其拉氏变换 F(s) 定义如下:F(s) = L{f(t)} = ∫[0,∞] f(t) * e^(-st) dt其中,s 是复频域变量,它可以是实数或复数。

拉氏变换后的函数 F(s) 表示了原始函数 f(t) 在复频域上的频谱特性。

MATLAB中的拉氏变换MATLAB提供了多个函数和工具箱,可以方便地进行拉氏变换的计算和分析。

下面介绍几个常用的函数和工具箱。

1. laplace函数laplace函数是MATLAB中用于计算拉氏变换的函数。

它的语法如下:F = laplace(f)其中,f 是输入函数,F 是输出函数。

laplace函数会自动计算函数 f 的拉氏变换,并返回结果。

2. ilaplace函数ilaplace函数是MATLAB中用于计算拉氏逆变换的函数。

它的语法如下:f = ilaplace(F)其中,F 是输入函数,f 是输出函数。

ilaplace函数会自动计算函数 F 的拉氏逆变换,并返回结果。

3. Control System ToolboxControl System Toolbox 是MATLAB中的一个工具箱,提供了丰富的函数和工具,用于分析和设计控制系统。

它包含了多个函数,可以方便地进行拉氏变换和控制系统分析。

使用 Control System Toolbox,可以进行拉氏变换的计算、绘制频率响应曲线、计算系统的稳定性等。

拉普拉斯变换-精选文档

拉普拉斯变换-精选文档

1 5 6 所 F 以 ( s ) s 1s 2s 3
共轭极点出现在 α jβ K K 1 2 F s ...... s α j β s α j β F α jβ 1 K s α j β F s 1 s α j β 2jβ
10


2 2 s 3 s 3 ( s 1 ) 1 所以 k 1 1 ( s 1 )( s 2 )( s 3 )s 1
同 : k 理 ( s 2 ) F ( s ) 5 , 2 s 2
k ( s 3 ) F ( s ) 6 3 s 3



L t t te d
st 0
1 st t de s 0
1 1 st 1 e 2 s s 0 s n 2 2 21 2 2 L t L t 2 3 s ss s n 3 3 2 32 6 3 L t L t 3 4 s ss s n! n 所 以 L t n1 s

σ α
st L t t e d t 1 全s域平面收敛
L t t t t e d t e 0 0
st 0
st 0
4.tnu(t)
L t t t e d
n st 0
三.拉氏逆变换的过程
找出 F s 的极点
s展 成 部 分 分 式 将 F
查拉氏变换表求 f t
第 页
7
四.部分分式展开法(m<n)
1.第一种情况:单阶实数极点
A ( s ) F ( s ) ( s p )( s p ) ( s p ) 1 2 n

4_2_4拉普拉斯变换法

4_2_4拉普拉斯变换法

解 F (s) = 1 − 1 s − 1 (s − 2)2
f (t ) = L−1[ 1 ] − L−1[ 1 ]
s−1
(s − 2)2
= et − t e2t (t ≥ 0).
版权归北京科技大学应用数学系 胡志兴
§1 Definition of Laplace Transform
(二)拉普拉斯变换法(求非齐次线性方程的特解 )
L−1[c1 F1 (s) + c2 F2 (s)] = c1 L−1[F1 (s)] + c2 L−1[F2 (s)]
L−1[c1 F1 (s) + c2 F2 (s)]


∫ ∫ = L−1[c1 e−st f1 (t ) d t + c2 e−st f2 (t ) d t]
0
0

∫ = L−1[ e−st (c1 f1 (t ) + c2 f2 (t )) d t]
版权归北京科技大学应用数学系 胡志兴
2 原函数的微分性质
§1 Definition of Laplace Transform
如果 f (t ), f ′(t ),", f (n)(t) 都是原函数,则有
L[ f ′(t )] = sL[ f (t )] − f (0) 或
L[ f (n)(t )]
= sn L[ f (t )] − sn−1 f (0) − sn−2 f ′(0) − " − f (n−1)(0)
§1 Definition of Laplace Transform
F (s) = L[ f (t )],

∫ F ′(s) = − t e−st f (t ) d t,

拉氏逆变换的性质

拉氏逆变换的性质拉普拉斯变换(英文:laplace transform),是工程数学中常用的一种积分变换。

如果定义:f(t),就是一个关于t,的函数,使当t\uc0,时候,f(t)=0,;s, 是一个复变量;mathcal 就是一个运算符号,它代表对其对象展开拉普拉斯分数int_0^infty e^ ,dt;f(s),就是f(t),的拉普拉斯转换结果。

f(t),的拉普拉斯变换由下列式子给出:f(s),=mathcal left =int_ ^infty f(t),e^ ,dt拉普拉斯逆变换,是已知f(s),,求解f(t),的过程。

用符号 mathcal ^ ,表示。

拉普拉斯连分数的公式就是:对于所有的t\ue0,;f(t)= mathcal ^ left=frac int_ ^ f(s),e^ ,dsc,是收敛区间的横坐标值,是一个实常数且大于所有f(s),的个别点的实部值。

为精简排序而创建的实变量函数和为丛藓科扭口藓变量函数间的一种函数转换。

对一个实变量函数并作拉普拉斯转换,并在复数域中并作各种运算,再将运算结果并作拉普拉斯反转换去求出实数域中的适当结果,往往比轻易在实数域中算出同样的结果在排序上难得多。

拉普拉斯转换的这种运算步骤对于解线性微分方程尤为有效率,它可以把微分方程化成难解的代数方程去处置,从而并使排序精简。

在经典掌控理论中,对控制系统的分析和综再分,都就是创建在拉普拉斯转换的基础上的。

导入拉普拉斯转换的一个主要优点,就是可以使用传递函数替代微分方程去叙述系统的特性。

这就为使用直观和方便快捷的图解方法去确认控制系统的整个特性(见到信号流程图、动态结构图)、分析控制系统的运动过程(见到奈奎斯特平衡帕累托、根轨迹法),以及综合控制系统的校正装置(见到控制系统校正方法)提供更多了可能性。

用 f(t)表示实变量t的一个函数,f(s)表示它的拉普拉斯变换,它是复变量s=σ+j&owega;的一个函数,其中σ和&owega; 均为实变数,j2=-1。

拉普拉斯变换(推荐完整)


f
-st
(t)e a dt

1
F(
s
)
aa
收敛域:
Re(s/a) s0 Re(s) as0
3)时移特性(Time Shifting)
若 f (t) L F (s) Re( s) s 0
则有 f (t - t0 )u(t - t0 ) L e-st0 F (s) t0 0, Re(s) s 0
例:求信号f
(t)

sin 0
t
0 t 其它

的Laplace变换。
f (t) sin(t)u(t) sin(t - )u(t - )
F
(
s)

1 s2
e - s 1
Re(s) -
例:单边周期信号的Laplace变换。 f(t)
单边周期信号的定义:
f(t)=f(t+nT); t0, n=0,1,2,...
拉普拉斯变换 (the Laplace Transform)
1、从傅里叶变换到拉普拉斯变换
傅里叶分析具有清晰的物理意义,但某些信号的傅里 叶变换不存在 (t<0,无意义的函数)。引入拉普拉斯变换, 从而也可以对这些信号进行分析。拉普拉斯变换实质 是将信号f(t)乘以衰减因子e-s t的傅里叶分析。
L[cos(w0t)u(t)]
s
s2

w
2 0
Re(s) 0
L[sin(w0t)u(t)]
w0
s2

w
2 0
Re(s) 0
单边拉普拉斯的基本性质 (properties of Laplace Transform)
1 ) 线性特性(linearity)

拉普拉斯变换讲解

bt
Re[s] > −b
−b

b σ
1 e u (−t ) ↔ − , Re[ s ] < +b s −b
1 1 X (s) = − s+b s−b
上述ROC有公共部分, 有公共部分, 当 b > 0 时,上述 有公共部分
−b < Re[ s ] < b
无公共部分, 当 b < 0 时,上述 ROC 无公共部分,表明 X (s) 不存在。 不存在。
1 例3. X ( s ) = 2 s + 3s + 2 1 1 = − s +1 s + 2

−2
−1
σ
ROC: 可以形成三种 ROC: 1) ROC: Re[ s ] > −1 : 2) ROC:Re[ s ] < −2 : 3) ROC: 2 < Re[ s] < −1 : − 右边信号。 此时x ( t ) 是右边信号。 左边信号。 此时 x ( t )是左边信号。 双边信号。 此时x ( t ) 是双边信号。
是右边信号, 若 x (t ) 是右边信号, T ≤ t < ∞ , σ 0在ROC内, 内 绝对可积, 则有 x (t )e −σ 0t 绝对可积,即:


T
x (t ) e − σ 0 t dt < ∞
若σ 1 > σ 0 ,则

T
∞ T
x ( t ) e − σ 1t d t
−σ 0t − (σ1 −σ 0 ) t
0 −at −st −∞
x (t ) = e − at u (t ) = u (t ) 当 a = 0时, 1 Re[ s ] > 0 可知 u ( t ) ↔ s

完整版拉普拉斯变换表

完整版拉普拉斯变换表拉普拉斯变换是一种重要的数学工具,它能将时间域上的函数转换为频率域上的函数,为信号处理、电路分析等领域的数学建模和分析提供了极大的便利。

下面是完整版的拉普拉斯变换表,列出了常用的函数及其对应的拉普拉斯变换公式。

1. 常数函数:f(t) = 1,其拉普拉斯变换为:F(s) = 1/s2. 单位阶跃函数:f(t) = u(t),其拉普拉斯变换为:F(s) = 1/s3. 指数函数:f(t) = e^-at,其拉普拉斯变换为:F(s) = 1/(s + a)4. 正弦函数:f(t) = sin(ωt),其拉普拉斯变换为:F(s) = ω/(s^2 + ω^2)5. 余弦函数:f(t) = cos(ωt),其拉普拉斯变换为:F(s) = s/(s^2 + ω^2)6. 指数衰减正弦函数:f(t) = e^-at sin(ωt),其拉普拉斯变换为:F(s) = ω/( (s+a)^2 + ω^2 )7. 指数衰减余弦函数:f(t) = e^-at cos(ωt),其拉普拉斯变换为:F(s) = (s+a)/( (s+a)^2 + ω^2 )8. 阻尼正弦函数:f(t) = e^-αt sin(ωt),其拉普拉斯变换为:F(s) = ω/( (s+α)^2 + ω^2 )9. 阻尼余弦函数:f(t) = e^-αt cos(ωt),其拉普拉斯变换为:F(s) = (s+α)/( (s+α)^2 + ω^2 )10. 给定函数f(t)的导数Laplace变换:f'(t) 的Laplace 变换 F(s) 为:F(s)= s*F(s) - f(0)11. 给定函数f(t)的不定积分Laplace变换:∫f(t)dt 的 Laplace 变换 F(s) 为:F(s)= 1/s*F(s)12. Laplace变换与乘法定理:L{f(t) g(t)} = F(s)G(s)13. Laplace变换与移位定理:L{f(t-a) u(t-a)} = e^-as F(s)14. Laplace变换与初值定理:f(0+) = lims→∞ sF(s)f'(0+) = lims→∞ s^2F(s) - sf(0+)f''(0+) = lims→∞ s^3F(s) - s^2f(0+) - sf'(0+)15. Laplace变换与终值定理:limt→∞ f(t) = lims→0 sF(s)limt→∞ f'(t) = lims→0 s^2F(s) - sf(0+)limt→∞ f''(t) = lims→0 s^3F(s) - s^2f(0+) -sf'(0+)这是完整版的拉普拉斯变换表,其中列出了常用的函数及其对应的拉普拉斯变换公式,以及常见的拉普拉斯变换定理和公式。

  1. 1、下载文档前请自行甄别文档内容的完整性,平台不提供额外的编辑、内容补充、找答案等附加服务。
  2. 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
  3. 3、如文档侵犯您的权益,请联系客服反馈,我们会尽快为您处理(人工客服工作时间:9:00-18:30)。

Laplace transformIn mathematics, the Laplace transform is a widely used integral transform. It has many important applications in mathematics, physics, economics, engineering, and probability theory.The Laplace transform is related to the Fourier transform, but whereas the Fourier transform resolves a function or signal into its modes of vibration, the Laplace transform resolves a function into its moments. Like the Fourier transform, the Laplace transform is used for solving differential and integral equations. In physics and engineering, it is used for analysis of linear time-invariant systems such as electrical circuits, harmonic oscillators, optical devices, and mechanical systems. In this analysis, the Laplace transform is often interpreted as a transformation from the time-domain, in which inputs and outputs are functions of time, to the frequency-domain, where the same inputs and outputs are functions of complex angular frequency, in radians per unit time. Given a simple mathematical or functional description of an input or output to a system, the Laplace transform provides an alternative functional description that often simplifies the process of analyzing the behavior of the system, or in synthesizing a new system based on a set of specifications.Denoted , it is a linear operator on a function f(t) (original) with a real argument t (t≥ 0) that transforms it to a function F(s) (image) with a complex argument s. This transformation is essentially bijective for the majority of practical uses; the respective pairs of f(t) and F(s) are matched in tables. The Laplace transform has the useful property that many relationships and operations over the originals f(t) correspond to simpler relationships and operations over the images F(s).[1]HistoryThe 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 formas 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 formwhich some modern historians have interpreted within modern Laplace transform theory.[3][4]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]Formal definitionThe 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 writeswhere the lower limit of 0− is short notation to meanThis 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.Probability theoryIn 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 expectationBy 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.Bilateral Laplace transformWhen 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:Inverse Laplace transformThe 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 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.Region of convergenceIf 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 limitexists. The Laplace transform converges absolutely if the integralexists (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{s}. Therefore the region ofconvergence 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{s}, the Laplace transform of ƒ can be expressed by integrating by parts as the integralThat 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.Properties and theoremsThe 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 transformTime domain 's' domain Comment Linearity Can be proved using basic rules ofintegration.Frequencydifferentiationis the first derivative of .Frequencydifferentiation More general form, n th derivative of F(s).Differentiationƒ is assumed to be a differentiablefunction, and its derivative is assumedto be of exponential type. This can thenbe obtained by integration by partsSecondDifferentiation ƒ is assumed twice differentiable and the second derivative to be of exponential type. Follows by applying the Differentiation property to .GeneralDifferentiation ƒ is assumed to be n-times differentiable, with n th derivative of exponential type. Follow by mathematical induction.FrequencyintegrationIntegrationis the Heaviside step function.Note is the convolution ofand .Scaling where is positive.FrequencyshiftingTime shiftingis the Heaviside step function Multiplicationthe integration is done along the verticalline that lies entirelywithin the region of convergence ofF.[12]Convolutionƒ(t ) and g (t ) are extended by zero fort < 0 in the definition of the convolution.PeriodicFunctionis a periodic function of period so that.This is the result of the time shifting property and the geometric series.•Initial value theorem :•Final value theorem :, if all poles ofare 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. or) the behaviour of this formula is undefined.Proof of the Laplace transform of a function's derivativeIt 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:yieldingand in the bilateral case,The general resultwhere f n is the n -th derivative of f , can then be established with an inductive argument.Evaluating improper integralsLet, then (see the table above)orLet we get the identityFor example,Another example is Dirichlet integral.Relationship to other transformsLaplace –Stieltjes transformThe (unilateral) Laplace –Stieltjes transform of a function g : R → R is defined by the Lebesgue –Stieltjes integralThe 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]Fourier transformThe continuous Fourier transform is equivalent to evaluating the bilateral Laplace transform with complex argument s = i ω 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 /(s 2 + ω02) whose ROC is Re(s ) > 0. Therefore, substituting s = i ω in F (s ) does not yield the Fourier transform of f (t ) = cos(ω0t ).However, a relation of the formholds 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.The Mellin transform and its inverse are related to the two-sided Laplace transform by a simple change of variables. If in the Mellin transformwe set θ = e-t we get a two-sided Laplace transform.Z-transformThe unilateral or one-sided Z-transform is simply the Laplace transform of an ideally sampled signal with the substitution ofwhere is the sampling period (in units of time e.g., seconds) and is the sampling rate (in samples per second or hertz)Letbe a sampling impulse train (also called a Dirac comb) andbe the continuous-time representation of the sampledare the discrete samples of .The Laplace transform of the sampled signal isThis is precisely the definition of the unilateral Z-transform of the discrete functionwith 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.The integral form of the Borel transformis a special case of the Laplace transform for ƒ an entire function of exponential type, meaning thatfor 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.Fundamental relationshipsSince 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.Table of selected Laplace transformsThe 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.IDFunctionTime domainLaplace s-domainRegion of convergence1ideal delay1a unit impulse2delayed n th powerwith frequency shift 2an th power( for integer n )2a.1q th power( for complex q )2a.2unit step2bdelayed unit step2c ramp2dn th power with frequency shift2d.1exponential decay 3exponential approach4sine 5cosine 6hyperbolic sine 7hyperbolic cosine 8Exponentially-decayingsine wave 9Exponentially-decayingcosine wave10n th root 11natural logarithm 12Bessel function of the first kind,of order n 13Modified Bessel functionof the first kind,of order n 14Bessel function of the second kind,of order 015Modified Bessel function of the second kind,of order 016Error functionExplanatory 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 is its real part.•, , , and are real numbers.•, is an integer.s-Domain equivalent circuits and impedancesThe 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.Examples: How to apply the properties and theoremsA few worked examples are provided here to enable the reader to assess comprehension of the factualpresentation. Elaboration beyond the role of supporting factual comprehension belongs at Wikiversity or Wikibooks.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.The following examples, derived from applications in physics and engineering, will use SI units of measure. SI is based on meters for distance, kilograms for mass, seconds for time, and amperes for electric current.Example #1: Solving a differential equationThe following example is based on concepts from nuclear physics.Consider the following first-order, linear differential equation:This equation is the fundamental relationship describing radioactive decay, whererepresents the number of undecayed atoms remaining in a sample of a radioactive isotope at time t (in seconds), and is the decay constant.We can use the Laplace transform to solve this equation.Rearranging the equation to one side, we haveNext, we take the Laplace transform of both sides of the equation:whereandSolving, we findFinally, we take the inverse Laplace transform to find the general solutionwhich is indeed the correct form for radioactive decay.Example #2: Deriving the complex impedance for a capacitorThis example is based on the principles of electrical circuit theory.The constitutive relation governing the dynamic behavior of a capacitor is the following 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 obtainwhereandSolving for V(s) we haveThe 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 Vat zero:oUsing this definition and the previous equation, we find:which is the correct expression for the complex impedance of a capacitor.Example #3: Method of partial fraction expansionConsider a linear time-invariant system with transfer functionThe 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 getThen by letting s = −α, the contribution from R vanishes and all that is left isSimilarly, the residue R is given byNote thatand so the substitution of R and P into the expanded expression for H(s) givesFinally, 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.Example #4: Mixing sines, cosines, and exponentialsTime function Laplace transformStarting with the Laplace transformwe find the inverse transform by first adding and subtracting the same constant α to the numerator:By the shift-in-frequency property, we haveFinally, using the Laplace transforms for sine and cosine (see the table, above), we haveExample #5: Phase delayTime function Laplace transformStarting 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:We can apply similar logic to find thatSee 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 integrationNotes[1]Korn & Korn 1967, §8.1[2]Euler 1744, (1753) and (1769)[3]Lagrange 1773[4]Grattan-Guinness 1997, p. 260[5]Grattan-Guinness 1997, p. 261[6]Grattan-Guinness 1997, pp. 261–262[7]Grattan-Guinness 1997, pp. 262–266[8]Feller 1971, §XIII.1[9]Widder 1941, Chapter II, §1[10]Widder 1941, Chapter VI, §2[11](Korn & Korn 1967, p. 226–227)[12]Bracewell 2000, Table 14.1, p. 385[13]Feller 1971, p. 432ReferencesModern•Arendt, Wolfgang; Batty, Charles J.K.; Hieber, Matthias; Neubrander, Frank (2002), Vector-Valued Laplace Transforms and Cauchy Problems, Birkhäuser Basel, ISBN 3764365498.•Bracewell, R. N. (2000), The Fourier Transform and Its Applications (3rd ed.), Boston: McGraw-Hill, ISBN 0071160434.•Davies, Brian (2002), Integral transforms and their applications (Third ed.), New York: Springer, ISBN 0-387-95314-0.•Feller, William (1971), An introduction to probability theory and its applications. Vol. II., Second edition, New York: John Wiley & Sons, MR0270403.•Korn, G.A.; Korn, T.M. (1967), Mathematical Handbook for Scientists and Engineers (2nd ed.), McGraw-Hill Companies, ISBN 0-0703-5370-0.•Polyanin, A. D.; Manzhirov, A. V. (1998), Handbook of Integral Equations, Boca Raton: CRC Press, ISBN 0-8493-2876-4.•Schwartz, Laurent (1952), "Transformation de Laplace des distributions", Comm. Sém. Math. Univ. Lund [Medd.Lunds Univ. Mat. Sem.]1952: 196–206, MR0052555.•Siebert, William McC. (1986), Circuits, Signals, and Systems, Cambridge, Massachusetts: MIT Press, ISBN 0-262-19229-2.•Widder, David Vernon (1941), The Laplace Transform, Princeton Mathematical Series, v. 6, Princeton University Press, MR0005923.•Widder, David Vernon (1945), "What is the Laplace transform?" (/stable/2305640), The American Mathematical Monthly (The American Mathematical Monthly, Vol. 52, No. 8) 52 (8): 419–425, doi:10.2307/2305640, MR0013447, ISSN 0002-9890.Historical•Deakin, M. A. B. (1981), "The development of the Laplace transform", Archive for the History of the Exact Sciences25: 343–390, doi:10.1007/BF01395660•Deakin, M. A. B. (1982), "The development of the Laplace transform", Archive for the History of the Exact Sciences26: 351–381•Euler, L. (1744), "De constructione aequationum", Opera omnia, 1st series 22: 150–161.•Euler, L. (1753), "Methodus aequationes differentiales", Opera omnia, 1st series 22: 181–213.•Euler, L. (1769), "Institutiones calculi integralis, Volume 2", Opera omnia, 1st series 12, Chapters 3-5.•Grattan-Guinness, I (1997), "Laplace's integral solutions to partial differential equations", in Gillispie, C. C., Pierre Simon Laplace 1749-1827: A Life in Exact Science, Princeton: Princeton University Press,ISBN 0-691-01185-0.•Lagrange, J. L. (1773), Mémoire sur l'utilité de la méthode, Œuvres de Lagrange, 2, pp. 171–234.External links•Online Computation (http://wims.unice.fr/wims/wims.cgi?lang=en&+module=tool/analysis/fourierlaplace.en) of the transform or inverse transform, wims.unice.fr•Tables of Integral Transforms (http://eqworld.ipmnet.ru/en/auxiliary/aux-inttrans.htm) at EqWorld: The World of Mathematical Equations.•Weisstein, Eric W., " Laplace Transform (/LaplaceTransform.html)" from MathWorld.•Laplace Transform Module by John H. Mathews (/mathews/c2003/ LaplaceTransformMod.html)•Good explanations of the initial and final value theorems (/e102/lectures/ Laplace_Transform/)•Laplace Transforms (/home/kmath508/kmath508.htm) at MathPages •Laplace and Heaviside (/Laplace/1a_lap_unitstepfns.php) at Interactive maths.•Laplace Transform Table and Examples (/Laplace.htm) at Vibrationdata.•Examples (/wiki/index.php/PDE:Laplace_Transforms) of solving boundary value problems (PDEs) with Laplace Transforms。

相关文档
最新文档