chapters laplace

numerical methods - 17.117. LAPLACE TRANSFORMS

17.1 INTRODUCTION

Laplace transforms provide a method for representing and analyzing linear sys-tems using algebraic methods. In systems that begin undeflected and at rest the Laplace s can directly replace the d/dt operator in differential equations. It is a superset of the phasor representation in that it has both a complex part, for the steady state response, but also a real part, representing the transient part. As with the other representations the Laplace s is related to the rate of change in the system.

Figure 17.1 The Laplace s

The basic definition of the Laplace transform is shown in Figure 17.2. The normal convention is to show the function of time with a lower case letter, while the same func-tion in the s-domain is shown in upper case. Another useful observation is that the trans-form starts at t=0s. Examples of the application of the transform are shown in Figure 17.3 for a step function and in Figure 17.4 for a first order derivative.

Topics:

Objectives: To be able to find time responses of linear systems using Laplace transforms.

Laplace transforms Using tables to do Laplace transforms Using the s-domain to find outputs Solving Partial Fractions

D s=

s j+=(if the initial conditions/derivatives are all zero at t=0s)

numerical methods - 17.2Figure 17.2 The Laplace transform

Figure 17.3 Proof of the step function transform

F s( ) f t( )e st td0

=

where,

F s( ) the function in terms of the Laplace s=f t( ) the function in terms of time t=

Aside: Proof of the step function transform.

F s( ) f t( )e st td0

5est

td0

5s---e

st

0

5s---e

s

5e s0

s------------

5s---= = = = =

For f(t) = 5,

numerical methods - 17.3Figure 17.4 Proof of the first order derivative transform

The previous proofs were presented to establish the theoretical basis for this method, however tables of values will be presented in a later section for the most popular transforms.

17.2 APPLYING LAPLACE TRANSFORMS

The process of applying Laplace transforms to analyze a linear system involves the basic steps listed below.

Aside: Proof of the first order derivative transform

Given the derivative of a function g(t)=df(t)/dt,

G s( ) L g t( )[ ] L ddt----- f t( ) (d/dt)f t( )est

td0

= = =we can use integration by parts to go backwards,

u vda

b

uv ab

v uda

b

=

(d/dt)f t( )e st td0

du df t( )=

therefore,

v est

=

u f t( )= dv sest dt=

f t( ) s( )e st td0

f t( )est

0


=


f t( )es f t( )e 0s[ ] s f t( )e st td

0

+=

L ddt----- f t( ) f 0( ) sL f t( )[ ]+=

numerical methods - 17.41. Convert the system transfer function, or differential equation, to the s-domain by replacing D with s. (Note: If any of the initial conditions are non-zero these must be also be added.)

2. Convert the input function(s) to the s-domain using the transform tables.3. Algebraically combine the input and transfer function to find an output function.4. Use partial fractions to reduce the output function to simpler components.5. Convert the output equation back to the time-domain using the tables.

17.2.1 A Few Transform Tables

Laplace transform tables are shown in Figure 17.5, Figure 17.7 and Figure 17.8. These are commonly used when analyzing systems with Laplace transforms. The trans-forms shown in Figure 17.5 are general properties normally used for manipulating equa-tions, and for converting them to/from the s-domain.

numerical methods - 17.5Figure 17.5 Laplace transform tables

L f t( )[ ]s

-----------------

Kf t( )

f1 t( ) f2 t( ) f3 t( ) + +

df t( )dt

-----------

d2f t( )dt2

--------------

dnf t( )dtn

--------------

f t( ) td0

t

KL f t( )[ ]

f1 s( ) f2 s( ) f3 s( ) + +

sL f t( )[ ] f 0( )

s2L f t( )[ ] sf 0( ) df 0

( )dt

------------------

snL f t( )[ ] sn 1 f 0( ) sn 2 df 0

( )dt

------------------

dn 1 f 0(dtn

-------------------------

TIME DOMAIN FREQUENCY DOMAIN

f t( ) f s( )

f t a( )u t a( ) a 0>,

f at( ) a 0>,

tf t( )

tnf t( )

f t( )t

--------

eas L f t( )[ ]

1a--- f s

a---

df s( )ds

---------------

1( )ndnf s( )dsn

---------------

f u( ) uds

eat f t( ) f s a( )

numerical methods - 17.6Figure 17.6 Drill Problem: Converting a differential equation to s-domain

The Laplace transform tables shown in Figure 17.7 and Figure 17.8 are normally used for converting to/from the time/s-domain.

L x 7x 8x+ + 9=[ ] =x 0( ) 1=x 0( ) 2=x 0( ) 3=

where,

numerical methods - 17.7Figure 17.7 Laplace transform tables (continued)

t( )

t

eat

t( )sin

t( )cos

teat

1

1s

2----

1s a+-----------

s2

2

+-----------------

s

s2

2

+-----------------

1s a+( )2

-------------------


A As---

unit impulse

step

ramp

exponential decay

t2 2

s3

----

tn

n 0>, n!s

n 1+-----------

t2e

at 2!s a+( )3

-------------------

numerical methods - 17.8Figure 17.8 Laplace transform tables (continued)

eat

t( )sin

eat

t( )cos

Bs C+s a+( )2 2+

--------------------------------

As j+-----------------------

Acomplex conjugate

s j+ +--------------------------------------+

As j+( )2

-------------------------------

Acomplex conjugate

s j+ +( )2--------------------------------------+

s a+( )2 2+--------------------------------

s a+

s a+( )2 2+--------------------------------

eat B tcos C aB

-----------------

tsin+

2 A e t t +( )cos

2t A e t t +( )cos


eat

t( )sin s a+( )2 2+

--------------------------------

s c+s a+( ) s b+( )---------------------------------

c a( )e at c b( )e btb a

---------------------------------------------------------

1s a+( ) s b+( )---------------------------------

eat

ebt

b a------------------------

numerical methods - 17.9Figure 17.9 Drill Problem: Converting from the time to s-domain

Figure 17.10 Drill Problem: Converting from the s-domain to time domain

17.3 MODELING TRANSFER FUNCTIONS IN THE s-DOMAIN

In previous chapters differential equations, and then transfer functions, were derived for mechanical and electrical systems. These can be converted to the s-domain, as

f t( ) 5 5t 8+( )sin=

f s( ) L f t( )[ ]= =

f s( ) 5s---

6s 7+-----------+=

f t( ) L 1 f s( )[ ]= =

numerical methods - 17.10shown in the mass-spring-damper example in Figure 17.11. In this case we assume the system starts undeflected and at rest, so the D operator may be directly replaced with the Laplace s. If the system did not start at rest and undeflected, the D operator would be replaced with a more complex expression that includes the initial conditions.

Figure 17.11 A mass-spring-damper example

Impedances in the s-domain are shown in Figure 17.12. As before these assume that the system starts undeflected and at rest.

Figure 17.12 Impedances of electrical components

KdKs

M x

F MD2x KdDx Ksx+ +=

F t( )x t( )---------- MD

2 KdD Ks+ +=

L F t( )x t( )----------

F s( )x s( )----------- Ms

2 Kds Ks+ += =F

ASIDE: Here D is simply replaced with s. Although this is very convenient, it is only valid if the initial conditions are zero, otherwise the more complex form, shown below, must be used.

L dnf t( )dtn

-------------- snL f t( )[ ] sn 1 f 0( ) sn 2 df 0

( )dt

------------------

dnf 0( )dtn

--------------------=

V s( ) RI s( )=V t( ) RI t( )=Resistor

V s( ) 1C---- I s( )

s---------=V t( ) 1C---- I t( ) td=Capacitor

V s( ) LsI s( )=V t( ) L ddt-----I t( )=Inductor

Time domain s-domainDevice

Z R=

Z 1sC------=

Z Ls=

Impedance

numerical methods - 17.11Figure 17.13 shows an example of circuit analysis using Laplace transforms. The circuit is analyzed as a voltage divider, using the impedances of the devices. The switch that closes at t=0s ensures that the circuit starts at rest. The calculation result is a transfer function.

Figure 17.13 A circuit example

At this point two transfer functions have been derived. To state the obvious, these relate an output and an input. To find an output response, an input is needed.

17.4 FINDING OUTPUT EQUATIONS

An input to a system is normally expressed as a function of time that can be con-verted to the s-domain. An example of this conversion for a step function is shown in Fig-ure 17.14.

Vi+-

L

CR

+Vo-

t=0sec

Treat the circuit as a voltage divider,

Vo

Vi 1

DC 1R---+

------------------

DL 1

DC 1R---+

------------------

+

---------------------------------------

ViR

1 DCR+----------------------

DLR R1 DCR+----------------------

+---------------------------------------------- Vi

RD2R2LC DLR R+ +-------------------------------------------------

= = =

VoVi------

Rs

2R2LC sLR R+ +---------------------------------------------

=

numerical methods - 17.12Figure 17.14 An input function

In the previous section we converted differential equations, for systems, to transfer functions in the s-domain. These transfer functions are a ratio of output divided by input. If the transfer function is multiplied by the input function, both in the s-domain, the result is the system output in the s-domain.

Figure 17.15 A transfer function multiplied by the input function

Output functions normally have complex forms that are not found directly in trans-form tables. It is often necessary to simplify the output function before it can be converted back to the time domain. Partial fraction methods allow the functions to be broken into

Apply a constant force of A, starting at time t=0 sec.(*Note: a force applied instantly is impossible but assumed)

F(t)= A for t >= 0= 0 for t < 0

F s( ) L F t( )[ ] As---= =

Perform Laplace transform using tables

Assume,Kd 3000

Nsm------=

Ks 2000Nm----=

M 1000kg=A 1000N=

x s( ) 1s

2 3s 2+ +( )s---------------------------------=

x s( )F s( )-----------

1Ms2 Kds Ks+ +--------------------------------------=

Given,

F s( ) As---=

Therefore,x s( ) x s( )

F s( )----------- F s( ) 1

Ms2 Kds Ks+ +--------------------------------------

A

s---= =

numerical methods - 17.13smaller, simpler components. The previous example in Figure 17.15 is continued in Figure 17.16 using a partial fraction expansion. In this example the roots of the third order denominator polynomial, are calculated. These provide three partial fraction terms. The residues (numerators) of the partial fraction terms must still be calculated. The example shows a method for finding resides by multiplying the output function by a root term, and then finding the limit as s approaches the root.

Figure 17.16 Partial fractions to reduce an output function

After simplification with partial fraction expansion, the output function is easily

x s( ) 1s

2 3s 2+ +( )s---------------------------------

1s 1+( ) s 2+( )s------------------------------------

As---

Bs 1+-----------

Cs 2+-----------+ += = =

A s 1s 1+( ) s 2+( )s------------------------------------

s 0lim 12

---= =

B s 1+( ) 1s 1+( ) s 2+( )s------------------------------------

s 1lim 1= =

C s 2+( ) 1s 1+( ) s 2+( )s------------------------------------

s 2lim 12

---= =

1s 1+( ) s 2+( )s------------------------------------

As---

Bs 1+-----------

Cs 2+-----------+ +=

s 1+( ) 1s 1+( ) s 2+( )s------------------------------------ s 1+( )

As--- s 1+( ) B

s 1+----------- s 1+( ) C

s 2+-----------+ +=

1s 2+( )s------------------- s 1+( )

As--- B s 1+( ) C

s 2+-----------+ +=

1s 2+( )s-------------------s 1lim s 1+( )

As---

s 1lim B

s 1lim s 1+( ) C

s 2+-----------

s 1lim+ +=

1s 2+( )s-------------------s 1lim Bs 1lim B= =

Aside: the short cut above can reduce time for simple partial fractionexpansions. A simple proof for finding B above is given in this box.

x s( ) 1s

2 3s 2+ +( )s---------------------------------

0.5s

-------

1s 1+-----------

0.5s 2+-----------+ += =

numerical methods - 17.14converted back to a function of time as shown in Figure 17.17.

Figure 17.17 Partial fractions to reduce an output function (continued)

17.5 INVERSE TRANSFORMS AND PARTIAL FRACTIONS

The flowchart in Figure 17.18 shows the general procedure for converting a func-tion from the s-domain to a function of time. In some cases the function is simple enough to immediately use a transfer function table. Otherwise, partial fraction expansion is nor-mally used to reduce the complexity of the function.

x t( ) L 1 x s( )[ ] L 1 0.5s

-------

1s 1+-----------

0.5s 2+-----------+ += =

x t( ) L 1 0.5s

------- L 1 1s 1+----------- L 1 0.5

s 2+-----------+ +=

x t( ) 0.5[ ] 1( )e t[ ] 0.5( )e 2t[ ]+ +=

x t( ) 0.5 e t 0.5e 2t+=

numerical methods - 17.15Figure 17.18 The methodology for doing an inverse transform of an output function

Figure 17.19 shows the basic procedure for partial fraction expansion. In cases where the numerator is greater than the denominator, the overall order of the expression can be reduced by long division. After this the denominator can be reduced from a polyno-mial to multiplied roots. Calculators or computers are normally used when the order of the polynomial is greater than second order. This results in a number of terms with unknown resides that can be found using a limit or algebra based technique.

Start with a function of s. NOTE: This does not apply for transfer functions.

is thefunction in

the transform

Match the function(s) tothe form in the tableand convert to a timefunction

yes

no

yes

can thefunction besimplified?

tables?simplify thefunction

no

Use partial fractions tobreak the function intosmaller parts

Done

numerical methods - 17.16Figure 17.19 The methodology for solving partial fractions

Figure 17.20 shows an example where the order of the numerator is greater than the denominator. Long division of the numerator is used to reduce the order of the term until it is low enough to apply partial fraction techniques. This method is used infrequently because this type of output function normally occurs in systems with extremely fast response rates that are infeasible in practice.

start with a function thathas a polynomial numeratorand denominator

is theorder of the

numerator >=denominator?

yes

no

use long division toreduce the order of thenumerator

Find roots of the denominatorand break the equation intopartial fraction form withunknown values

Done

ORuse algebra techniqueuse limits technique.

If there are higher orderroots (repeated terms)then derivatives will berequired to find solutions

numerical methods - 17.17Figure 17.20 Partial fractions when the numerator is larger than the denominator

Partial fraction expansion of a third order polynomial is shown in Figure 17.21. The s-squared term requires special treatment. Here it produces partial two partial fraction terms divided by s and s-squared. This pattern is used whenever there is a root to an expo-nent.

x s( ) 5s3 3s2 8s 6+ + +

s2 4+

--------------------------------------------=

This cannot be solved using partial fractions because the numerator is 3rd order and the denominator is only 2nd order. Therefore long division can be used to reduce the order of the equation.

s2 4+ 5s3 3s2 8s 6+ + +

5s 3+

5s3 20s+

3s2 12s 6+3s2 12+

12s 6This can now be used to write a new function that has a reduced portion that can be

solved with partial fractions.

x s( ) 5s 3 12s 6s

2 4+----------------------+ += solve 12s 6

s2 4+

----------------------

As 2j+-------------

Bs 2j-------------+=

numerical methods - 17.18Figure 17.21 A partial fraction example

Figure 17.22 shows another example with a root to an exponent. In this case each of the repeated roots is given with the highest order exponent, down to the lowest order exponent. The reader will note that the order of the denominator is fifth order, so the resulting partial fraction expansion has five first order terms.

Figure 17.22 Partial fractions with repeated roots

Algebra techniques are a reasonable alternative for finding partial fraction resi-dues. The example in Figure 17.23 extends the example begun in Figure 17.22. The equiv-alent forms are simplified algebraically, until the point where an inverse matrix solution is used to find the residues.

x s( ) 1s

2s 1+( )

---------------------

As

2----

Bs---

Cs 1+-----------+ += =

C s 1+( ) 1s

2s 1+( )

---------------------

s 1lim 1= =

A s2 1s

2s 1+( )

---------------------

s 0lim 1

s 1+-----------

s 0lim 1= = =

B dds----- s

2 1s

2s 1+( )

---------------------

s 0lim dds

-----

1s 1+-----------

s 0lim s 1+( ) 2[ ]

s 0lim 1= = = =

F s( ) 5s

2s 1+( )3

------------------------=

5

s2

s 1+( )3------------------------

As

2----

Bs---

Cs 1+( )3

-------------------

Ds 1+( )2

-------------------

Es 1+( )----------------+ + + +=

numerical methods - 17.19Figure 17.23 Solving partial fractions algebraically

For contrast, the example in Figure 17.23 is redone in Figure 17.24 using the limit techniques. In this case the use of repeated roots required the differentiation of the output function. In these cases the algebra techniques become more attractive, despite the need to solve simultaneous equations.

5

s2

s 1+( )3------------------------

As

2----

Bs---

Cs 1+( )3

-------------------

Ds 1+( )2

-------------------

Es 1+( )----------------+ + + +=

A s 1+( )3 Bs s 1+( )3 Cs2 Ds2 s 1+( ) Es2 s 1+( )2+ + + +s

2s 1+( )3

------------------------------------------------------------------------------------------------------------------------------------------=

s4 B E+( ) s3 A 3B D 2E+ + +( ) s2 3A 3B C D E+ + + +( ) s 3A B+( ) A( )+ + + +

s2

s 1+( )3---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------=

0 1 0 0 11 3 0 1 23 3 1 1 13 1 0 0 01 0 0 0 0

ABCDE

00005

=

ABCDE

0 1 0 0 11 3 0 1 23 3 1 1 13 1 0 0 01 0 0 0 0

100005

51551015

= =

5

s2

s 1+( )3------------------------

5s

2----

15s

---------

5s 1+( )3

-------------------

10s 1+( )2

-------------------

15s 1+( )----------------+ + + +=

numerical methods - 17.20Figure 17.24 Solving partial fractions with limits

An inductive proof for the limit method of solving partial fractions is shown in Figure 17.25.

5

s2

s 1+( )3------------------------

As

2----

Bs---

Cs 1+( )3

-------------------

Ds 1+( )2

-------------------

Es 1+( )----------------+ + + +=

A 5

s2

s 1+( )3------------------------

s2s 0lim 5

s 1+( )3-------------------

s 0lim 5= = =

B dds-----

5

s2

s 1+( )3------------------------

s2s 0lim dds

-----

5s 1+( )3

-------------------

s 0lim 5 3( )

s 1+( )4-------------------

s 0lim 15= = = =

C 5

s2

s 1+( )3------------------------

s 1+( )3s 1lim 5

s2

----

s 1lim 5= = =

D 11!-----

dds-----

5

s2

s 1+( )3------------------------

s 1+( )3s 1lim 11!

-----

dds-----

5s

2----

s 1lim 11!

-----

2 5( )s

3--------------

s 1lim 10= = = =

E 12!-----

dds-----

2 5

s2

s 1+( )3------------------------

s 1+( )3s 1lim 12!

-----

dds-----

2 5s

2----

s 1lim 12!

-----

30s

4------

s 1lim 15= = = =

5

s2

s 1+( )3------------------------

5s

2----

15s

---------

5s 1+( )3

-------------------

10s 1+( )2

-------------------

15s 1+( )----------------+ + + +=

5

s2

s 1+( )3------------------------

As

2----

Bs---

Cs 1+( )3

-------------------

Ds 1+( )2

-------------------

Es 1+( )----------------+ + + +=s 1lim

s 1+( )3 5s

2s 1+( )3

------------------------

As

2----

Bs---

Cs 1+( )3

-------------------

Ds 1+( )2

-------------------

Es 1+( )----------------+ + + +=

s 1lim

5

s2

s 1+( )3------------------------

As

2----

Bs---

Cs 1+( )3

-------------------

Ds 1+( )2

-------------------

Es 1+( )----------------+ + + +=

5s

2----

A s 1+( )3s

2-----------------------

B s 1+( )3s

----------------------- C D s 1+( ) E s 1+( )2+ + + +=s 1lim

numerical methods - 17.21Figure 17.25 A proof of the need for differentiation for repeated roots

17.6 EXAMPLES

17.6.1 Mass-Spring-Damper Vibration

A mass-spring-damper system is shown in Figure 17.26 with a sinusoidal input.

For C, evaluate now,

51( )2

-------------

A 1 1+( )31( )2

----------------------------

B 1 1+( )31

---------------------------- C D 1 1+( ) E 1 1+( )2+ + + +=

51( )2

-------------

A 0( )31( )2

--------------

B 0( )31

-------------- C D 0( ) E 0( )2+ + + += C 5=

For D, differentiate once, then evaluate

ddt-----

5s

2----

A s 1+( )3s

2-----------------------

B s 1+( )3s

----------------------- C D s 1+( ) E s 1+( )2+ + + +=

s 1lim

2 5( )s

3-------------- A 2 s 1+( )

3

s3

----------------------

3 s 1+( )2

s2

----------------------+

B s 1+( )3

s2

-------------------

3 s 1+( )2s

----------------------+

D 2E s 1+( )+ + +=s 1lim

2 5( )1( )3

-------------- D 10= =

For E, differentiate twice, then evaluate (the terms for A and B will be ignored to save

ddt-----

2 5s

2----

A s 1+( )3

s2

-----------------------

B s 1+( )3s

----------------------- C D s 1+( ) E s 1+( )2+ + + +=

s 1lim

ddt-----

2 5( )s

3-------------- A ( ) B ( ) D 2E s 1+( )+ + += s 1lim

space, but these will drop out anyway).

3 2 5( )( )s

4------------------------- A ( ) B ( ) 2E+ +=

s 1lim

3 2 5( )( )1( )4

------------------------- A 0( ) B 0( ) 2E+ += E 15=

numerical methods - 17.22Figure 17.26 A mass-spring-damper example

The residues for the partial fraction in Figure 17.26 are calculated and converted to a function of time in Figure 17.27. In this case the roots of the denominator are complex, so the result has a sinusoidal component.

M 1kg= Ks 2Nm----= Kd 0.5

Nsm------=

The sinusoidal input is converted to the s-domain,

Component values are,

F t( ) 5 6t( )Ncos=

F s( ) 5ss

2 62+----------------=

This can be combined with the transfer function to obtain the output function,

x s( ) F s( ) x s( )F s( )-----------

5ss

2 62+----------------

11---

s2 0.5s 2+ +

------------------------------

= =

x s( ) 5ss

2 36+( ) s2 0.5s 2+ +( )----------------------------------------------------------=

x s( ) As 6j+-------------

Bs 6j-------------

Cs 0.25 1.39j+-------------------------------------

Ds 0.25 1.39j-------------------------------------+ + +=

x s( )F s( )-----------

1M-----

s2 Kd

M------s

KsM-----+ +

---------------------------------=

Given,

numerical methods - 17.23Figure 17.27 A mass-spring-damper example (continued)

17.6.2 Circuits

It is not necessary to develop a transfer functions for a system. The equation for the voltage divider is shown in Figure 17.28. Impedance values and the input voltage are con-verted to the s-domain and written in the equation. The resulting output function is manip-ulated into partial fraction form and the residues calculated. An inverse Laplace transform is used to convert the equation into a function of time using the tables.

A s 6j+( ) 5s( )s 6j( ) s 6j+( ) s2 0.5s 2+ +( )

-------------------------------------------------------------------------

s 6jlim 30j12j( ) 36 3j 2+( )-----------------------------------------------= =

A 73.2 10 3 3.05=

Continue on to find C, D same way

x s( ) 73.2 103 3.05

s 6j+-------------------------------------------73.2 10 3 3.05

s 6j---------------------------------------------- + +=

x t( ) 2 73.2 10 3( )e 0t 6t 3.05( )cos +=Do inverse Laplace transform

B A* 73.2 10 3 3.05= =

numerical methods - 17.24Figure 17.28 A circuit example

t=0

+-

+Vo-

Vs 3 tcos=

Vo VsZC

ZR ZC+-------------------

=

As normal, relate the source voltage to the output voltage using component values in the s-domain.

Vs s( )3s

s2 1+

--------------= ZR R= ZC1

sC------=

Next, equations are combined. The numerator of resulting output function must be reduced by long division.

Vo3s

s2 1+

--------------

1sC------

R 1sC------+

----------------

3ss

2 1+( ) 1 sRC+( )--------------------------------------------

3ss

2 1+( ) s10310 3 1+( )--------------------------------------------------------= = =

C 10 3 F=

R 103=

Vo3s

s2 1+( ) s 1+( )

-----------------------------------

As B+s

2 1+----------------

Cs 1+-----------+

As2 As Bs B Cs2 C+ + + + +s

2 1+( ) s 1+( )----------------------------------------------------------------------= = =

The output function can be converted to a partial fraction form and the residues calcu-lated.

Vo3s

s2 1+( ) s 1+( )

-----------------------------------

s2 A C+( ) s A B+( ) B C+( )+ +

s2 1+( ) s 1+( )

-----------------------------------------------------------------------------= =

B C+ 0= B C=A C+ 0= A C=A B+ 3= C C 3= C 1.5= A 1.5= B 1.5=

Vo1.5s 1.5+

s2 1+

------------------------

1.5s 1+-----------+=

numerical methods - 17.25Figure 17.29 A circuit example (continued)

17.7 ADVANCED TOPICS

17.7.1 Input Functions

In some cases a system input function is comprised of many different functions, as shown in Figure 17.30. The step function can be used to switch function on and off to cre-ate a piecewise function. This is easily converted to the s-domain using the e-to-the-s functions.

The output function can be converted to a function of time using the transform tables, as shown below.

Vo t( ) L1 Vo s( )[ ] L

1 1.5s 1.5+s

2 1+------------------------

1.5s 1+-----------+ L 1 1.5s 1.5+

s2 1+

------------------------ L 1 1.5s 1+-----------+= = =

V o t( ) 1.5L 1s

s2 1+

-------------- 1.5L 1 1s

2 1+-------------- 1.5e t+=

V o t( ) 1.5 tcos 1.5 tsin 1.5e t+=

V o t( ) 1.52 1.52+ t1.51.5-------

atan+ sin 1.5e t=

V o t( ) 2.121 t4---+

sin 1.5e t=

numerical methods - 17.26Figure 17.30 Switching on and off function parts

17.7.2 Initial and Final Value Theorems

The initial and final values an output function can be calculated using the theorems shown in Figure 17.31.

Figure 17.31 Final and initial values theorems

t

f(t)

5

0 1 3 4seconds

f t( ) 5tu t( ) 5 t 1( )u t 1( ) 5 t 3( )u t 3( ) 5 t 4( )u t 4( )+=

f s( ) 5s

2----

5e s

s2

----------

5e 3s

s2

------------

5e 4s

s2

------------+=

x t ( ) sx s( )[ ]s 0lim=

x t ( ) 1ss

2 3s 2+ +( )s---------------------------------

s 0lim 1

s2 3s 2+ +

--------------------------

s 0lim 1

0( )2 3 0( ) 2+ +-------------------------------------

12---= = = =

Final value theorem

x t 0( ) sx s( )[ ]s lim=

x t 0( ) 1 s( )s

2 3s 2+ +( )s---------------------------------

s lim 1

( )2 3 ( ) 2+ +( )--------------------------------------------

1

---- 0= = = =

Initial value theorem

numerical methods - 17.2717.8 A MAP OF TECHNIQUES FOR LAPLACE ANALYSIS

The following map is to be used to generally identify the use of the various topics covered in the course.

Figure 17.32 A map of Laplace analysis techniques

System Model(differential equations)

Laplace Transform

TransferFunction

Some inputdisturbance interms of time

Input described withLaplace Equation

We can figure

Steady state

Bode and Phase Plots- Straight line- Exact plot

Approximate equations forsteady state vibrations

Equations for gain and phaseat different frequencies

Phasor Transform

Substitute

Output Function(Laplace form)

Output Function(Laplace terms)Partial Fraction

Time based

Inverse Laplace

Root-Locusfor stability

responseequation

frequency response

out from plots

Experiments

numerical methods - 17.2817.9 SUMMARY

Transfer and input functions can be converted to the s-domain Output functions can be calculated using input and transfer functions Output functions can be converted back to the time domain using partial frac-

tions.

17.10 PRACTICE PROBLEMS

1. Convert the following functions from time to laplace functions using the tables.

L 5[ ]

L e 3t[ ]

L 5e 3t[ ]

L 5te 3t[ ]

L 5t[ ]

L 4t2[ ]

L 5t( )cos[ ]

L 5t 1+( )cos[ ]

L 5e 3t 5t( )cos[ ]

L 5e 3t 5t 1+( )cos[ ]

L 5t( )sin[ ]

L 3t( )sinh[ ]

a)

b)

c)

d)

e)

f)

g)

h)

i)

j)

k)

l)

L 3t3 t 1( ) e 5t+[ ]

L t2 2t( )sin[ ]

L ddt-----t

2e

3t

L x 5x 3x+ +[ ] x 0( ), 8 x 0( ), 7= =

L ddt----- 6t( )sin

L ddt-----

3t2

L y td0

t

L u t 1( ) u t 2( )[ ]

L e 2t u t 2( )[ ]

L e t 3( ) u t 1( )[ ]

L 5e 3t u t 1( ) u t 2( )+[ ]

L 7t 2+( )cos et 3+[ ]

s)

m)

n)

o)

p)

q)

r)

t)

u)

v)

w)

x)

L 3 t 1( ) e t 1+( )+[ ]

y)

L 6e 2.7t 9.2t 3+( )cos[ ]z)aa)

numerical methods - 17.292. Convert the following functions below from the laplace to time domains using the tables.

3. Convert the following functions below from the laplace to time domains using partial fractions and the tables.

4. Convert the output function below Y(s) to the time domain Y(t) using the tables.

L 1 1s 1+-----------a)

L 1 5s 1+-----------b)

L 1 6s

2----c)

L 1 6s

3----d)

L 1 s 2+s 3+( ) s 4+( )---------------------------------e)

L 1 6s

2 5s 6+ +--------------------------

f)

L 1 64s2 20s 24+ +-----------------------------------

g)

L 1 6s

2 6+--------------

h)

L 1 5s--- 1 e 4.5s( )

i)

L 1 4 3j+s 1 2j+----------------------

4 3js 1 2j+ +-----------------------+

j)

L 1 6s

4----

6s

2 9+--------------+

k)

L 1 s 2+s 3+( ) s 4+( )---------------------------------a)

L 1 [ ]b)

L 1 [ ]c)

L 1 [ ]d)

L 1 6s

2 5s+----------------e)

L 1 9s2 6s 3+ +

s3 5s2 4s 6+ + +

----------------------------------------f)

L 1 s3 9s2 6s 3+ + +

s3 5s2 4s 6+ + +

----------------------------------------g)

L 1 9s 4+s 3+( )3

-------------------h)

L 1 9s 4+s

3s 3+( )3

------------------------i)

L 1 s2 2s 1+ +

s2 3s 2+ +

--------------------------j)

L 1 s2 3s 5+ +6s2 6+

--------------------------k)

L 1 s2 2s 3+ +

s2 2s 1+ +

--------------------------l)

Y s( ) 5s---

12s

2 4+--------------

3s 2 3j+----------------------

3s 2 3j+ +-----------------------+ + +=

numerical methods - 17.305. Convert the following differential equations to transfer functions.

6. Given the transfer function, G(s), determine the time response output Y(t) to a step input X(t).

7. Given the following input functions and transfer functions, find the response in time.

8. Do the following conversions as indicated.

9. Convert the output function to functions of time.

10. Solve the differential equation using Laplace transforms. Assume the system starts unde-flected and at rest.

5x 6x 2x+ + 5F=a)y 8y+ 3x=b)y y 5x+ 0=c)

G s( ) 4s 2+-----------

Y s( )X s( )-----------= = X t( ) 20= When t >= 0

x s( )F s( )-----------

s 2+s 3+( ) s 4+( )---------------------------------

m

N----

=a) F t( ) 5N=

Transfer Function Input

x s( )F s( )-----------

s 2+s 3+( ) s 4+( )---------------------------------

m

N----

=b) x t( ) 5m=

L 5e 4 t 3t 2+( )cos[ ] =a)

b)

c)

d)

e)

L e 2t 5t u t 2( ) u t( )( )+[ ] =

L ddt-----

3y 2 ddt-----

y y+ + = where at t=0y0 1= y0' 2=

y0'' 3= y0''' 4=

L 1 1 j+s 3 4j+ +-----------------------

1 js 3 4j+----------------------+ =

L 1 s 1s 2+-----------

3s

2 4s 40+ +-----------------------------+ + =

s3 4s2 4s 4+ + +

s3 4s+

----------------------------------------

a)

s2 4+

s4 10s3 35s2 50s 24+ + + +

-------------------------------------------------------------------

b)

40 20 2+ + + 4=

numerical methods - 17.3117.11 PRACTICE PROBLEM SOLUTIONS

1.

2( )cos s 2( )sin 7s

2 49+--------------------------------------------

e3

s 1-----------+

0.416s 6.37s

2 49+-------------------------------------

e3

s 1-----------+=x)

3s

2----

3s---

e1

s 1+-----------+

y)

a) 5s---

1s 3+-----------

b)

5s 3+-----------

c)

d) 5s 3+( )2

-------------------

5s

2----

e)

8s

3----

f)

g) ss

2 25+-----------------

s 1cos 5 1sins

2 25+----------------------------------

h)

5 s 3+( )s 3+( )2 52+

------------------------------i)

2.5 1s 3 5j+----------------------

2.5 1s 3 5j+ +-----------------------+j)

k) 5s

2 25+-----------------

0.5s 3-----------

0.5s 3+-----------

l)

3 3s 2.7 9.2j+-------------------------------

3 3s 2.7 9.2j+ +--------------------------------+

s( ) +s

2 5.4s 91.93+ +-----------------------------------------=

z)

m) 4s

2 4+( )2---------------------

16s2

s2 4+( )3

---------------------+12s2 16

s2 4+( )3

-----------------------=

2ss 3+( )3

-------------------n)

s2x 7s 8( ) 5 sx 7( ) 3x+ +o)

p) 6ss

2 36+-----------------

2q)

ys--

r)

s) 72s

5------

18s

4------

1s 5+-----------+

es

s-------

e2s

s---------

t)

e4 2s

s 2+-------------

u)

5s 3+-----------

es

s-------

e2s

s---------

+w)

s( ) +s

2 6s 34+ +-----------------------------= e

2 s

s 1+-----------

v)

numerical methods - 17.322.

3.

4.

5.

a) e t

b) 5e t

c) 6t

d) 3t2

e) e 3t 2e 4t+

f)

6e 2t 6e 3tj)

2 5( )e 1( )t 2t 34--- atan+

cos

g)

1.5e 2t 1.5e 3t

h)

6 6t( )sin

i)

5 5u t 4.5( )

k)

t3 2 3t( )sin+

j) t( ) e 2tk) t( )6--------- 0.834 t 0.927+( )cos+

l) t( ) 2te t+

g)

h)

i)

d)

e) 1.2 1.2e 5t

f) 8.34e 4.4t 2 0.99( )e 0.3t 1.13t 1.23+( )cos+

a) e 3t 2e 4t+

b)

c)

y t( ) 5 6 2t( )sin 2 3( )e 2t 3t 0( )cos+ +=

x

F---

55s2 6s 2+ +-----------------------------=a)

yx--

3s 8+-----------=b)

yx--

5s 1-----------=c)


7.

8.

y t( ) 40 40e 2t=

56---

53---e

3t 52---e

4t+a)

5 t( ) 30 5e 2t+( )Nb)

L 5e 4 t 3t 2+( )cos[ ] L 2 A e t t +( )cos[ ]=

As j+-----------------------

Acomplex conjugate

s j+ +--------------------------------------+1.040 2.273j+

s 4 3j+---------------------------------------1.040 2.273j

s 4 3j+ +---------------------------------------+=

A 2.5=

a) 4= 3=

2=

A 2.5 2cos 2.5j 2sin+ 1.040 2.273j+= =

L e 2t 5t u t 2( ) u t( )( )+[ ] L e 2t[ ] L 5tu t 2( )[ ] L 5tu t( )[ ]+=b)

1s 2+----------- 5L tu t 2( )[ ] 5

s2

----+

1s 2+----------- 5L t 2( )u t 2( ) 2u t 2( )+[ ] 5

s2

----+= =

1s 2+----------- 5L t 2( )u t 2( )[ ] 10L u t 2( )[ ] 5

s2

----+ +=

1s 2+----------- 5e 2s L t[ ] 10e 2s L 1[ ] 5

s2

----+ +=

1s 2+-----------

5e 2s

s2

------------

10e 2s

s---------------

5s

2----

+ +=

c) ddt-----

3y s3y 1s2 2s1 3s0+ + +=

ddt-----

y s1y s01+=

L ddt-----

3y 2 ddt-----

y y+ + s3y 1s2 2s 3+ + +( ) sy 1+( ) y( )+ +=

y s3 s 1+ +( ) s2 2s 4+ +( )+=

numerical methods - 17.34

9.

L 1 1 j+s 3 4j+ +-----------------------

1 js 3 4j+----------------------+ L

1 As j+-----------------------

Acomplex conjugate

s j+ +--------------------------------------+=

2 A e t t +( )cos 2.282e 3t 4t 4--- cos= =

d)

A 12 12+ 1.141= = 1

1------

atan 4---

= = 3= 4=

L 1 s 1s 2+-----------

3s

2 4s 40+ +-----------------------------+ + L s[ ] L 1

s 2+----------- L 3

s2 4s 40+ +

-----------------------------+ +=e)

ddt----- t( ) e 2t L 3

s 2+( )2 36+-------------------------------+ +

ddt----- t( ) e 2t 0.5L 6

s 2+( )2 36+-------------------------------+ += =

ddt----- t( ) e 2t 0.5e 2t 6t( )sin+ +=

s3 4s2 4s 4+ + +

s3 4s+

----------------------------------------

a)s

3 4s2 4s 4+ + +s3 4s+s

3 4s+( )

1

4s2 4+

1 4s2 4+

s3 4s+

-----------------+ 1 As---

Bs C+s

2 4+----------------+ + 1 s

2 A B+( ) s C( ) 4A( )+ +s

3 4s+-----------------------------------------------------------+= = =

A 1=C 0=B 3=

1 1s---

3ss

2 4+--------------+ +=

t( ) 1 3 2t( )cos+ +=


17.12 ASSIGNMENT PROBLEMS

1. Prove the following relationships.

s2 4+

s4 10s3 35s2 50s 24+ + + +

-------------------------------------------------------------------

As 1+-----------

Bs 2+-----------

Cs 3+-----------

Ds 4+-----------+ + +=

b)

A s2 4+

s 2+( ) s 3+( ) s 4+( )--------------------------------------------------

s 1lim 56

---= =

B s2 4+

s 1+( ) s 3+( ) s 4+( )--------------------------------------------------

s 2lim 82

------= =

C s2 4+

s 1+( ) s 2+( ) s 4+( )--------------------------------------------------

s 3lim 132

------= =

D s2 4+

s 1+( ) s 2+( ) s 3+( )--------------------------------------------------

s 4lim 206

------= =

56---e

t 4e 2t 132------e

3t 103------e

4t+

t( ) 66 10 6 e 39.50t 3.216e0.1383t 1.216e 0.3368t 2.00+ +=

L f ta---

aF as( )=a)

L f at( )[ ] 1a---F s

a---

=b)

L e at f t( )[ ] F s a+( )=c)

f t( )t lim sF s( )

s 0lim=d)

f t( )t lim sF s( )

s 0lim=e)

L tf t( )[ ] ddt-----F s( )=f)

numerical methods - 17.362. The applied force F is the input to the system, and the output is the displacement x.

b) What is the steady state response for an applied force F(t) = 10cos(t + 1) N ?c) Give the transfer function if x is the input.d) Find x(t), given F(t) = 10N for t >= 0 seconds using Laplace methods.

3. The following differential equation is supplied, with initial conditions.

a) Solve the differential equation using calculus techniques.b) Write the equation in state variable form and solve it numerically.c) Find the frequency response (gain and phase) for the transfer function using the

phasor transform. Roughly sketch the bode plots.d) Convert the differential equation to the Laplace domain, including initial condi-

tions. Solve to find the time response.

4. Given the transfer functions and input functions, F, use Laplace transforms to find the output of the system as a function of time. Indicate the transient and steady state parts of the solution.

K1 = 500 N/m

K2 = 1000 N/mx

M = 10kg

F

a) find the transfer function.

y y 7y+ + F= y 0( ) 1= y 0( ) 0=

F t( ) 10= t 0>

x

F---

D2

D 200+( )2------------------------------= F 5 62.82t( )sin=

x

F---

D D 2+( )D 200+( )2

------------------------------= F 5 62.82t( )sin=

numerical methods - 17.37

17.13 REFERENCES

Irwin, J.D., and Graf, E.R., Industrial Noise and Vibration Control, Prentice Hall Publishers, 1979.

Close, C.M. and Frederick, D.K., Modeling and Analysis of Dynamic Systems, second edition, John Wiley and Sons, Inc., 1995.

x

F---

D2 D 2+( )D 200+( )2

------------------------------= F 5 62.82t( )sin=

chapters laplace

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