THE LAPLACE TRANSFORM

Similar documents
Chapter 12 Introduction To The Laplace Transform

DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS. Assoc. Prof. Dr. Burak Kelleci. Spring 2018

Transfer function and the Laplace transformation

Chap.3 Laplace Transform

Chapter 5 The Laplace Transform. x(t) input y(t) output Dynamic System

LaPlace Transform in Circuit Analysis

2. The Laplace Transform

Instructors Solution for Assignment 3 Chapter 3: Time Domain Analysis of LTIC Systems

Final Exam : Solutions

REPETITION before the exam PART 2, Transform Methods. Laplace transforms: τ dτ. L1. Derive the formulas : L2. Find the Laplace transform F(s) if.

Boyce/DiPrima 9 th ed, Ch 2.1: Linear Equations; Method of Integrating Factors

Partial Fraction Expansion

Why Laplace transforms?

Elementary Differential Equations and Boundary Value Problems

Laplace Transform. National Chiao Tung University Chun-Jen Tsai 10/19/2011

Boyce/DiPrima/Meade 11 th ed, Ch 6.1: Definition of Laplace Transform

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule

CSE 245: Computer Aided Circuit Simulation and Verification

Midterm exam 2, April 7, 2009 (solutions)

Lecture 4: Laplace Transforms

Laplace Transforms recap for ccts

INTRODUCTION TO AUTOMATIC CONTROLS INDEX LAPLACE TRANSFORMS

Let s look again at the first order linear differential equation we are attempting to solve, in its standard form:

Poisson process Markov process

MEM 355 Performance Enhancement of Dynamical Systems A First Control Problem - Cruise Control

Chapter 9 The Laplace Transform

Ma/CS 6a Class 15: Flows and Bipartite Graphs

EECE 301 Signals & Systems Prof. Mark Fowler

6.8 Laplace Transform: General Formulas

fiziks Institute for NET/JRF, GATE, IIT JAM, JEST, TIFR and GRE in PHYSICAL SCIENCES MATEMATICAL PHYSICS SOLUTIONS are

[ ] 1+ lim G( s) 1+ s + s G s s G s Kacc SYSTEM PERFORMANCE. Since. Lecture 10: Steady-state Errors. Steady-state Errors. Then

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship

Spring 2006 Process Dynamics, Operations, and Control Lesson 2: Mathematics Review

Boyce/DiPrima 9 th ed, Ch 7.8: Repeated Eigenvalues

where: u: input y: output x: state vector A, B, C, D are const matrices

Lecture 26: Leapers and Creepers

4.1 The Uniform Distribution Def n: A c.r.v. X has a continuous uniform distribution on [a, b] when its pdf is = 1 a x b

Sample Final Exam (finals03) Covering Chapters 1-9 of Fundamentals of Signals & Systems

S.Y. B.Sc. (IT) : Sem. III. Applied Mathematics. Q.1 Attempt the following (any THREE) [15]

Problem 2. Describe the following signals in terms of elementary functions (δ, u,r, ) and compute. x(t+2) x(2-t) RT_1[x] -3-2 = 1 2 = 1

Chapter 13 Laplace Transform Analysis

ECE Spring Prof. David R. Jackson ECE Dept. Notes 6

Voltage v(z) ~ E(z)D. We can actually get to this wave behavior by using circuit theory, w/o going into details of the EM fields!

14.02 Principles of Macroeconomics Fall 2005 Quiz 3 Solutions

PID Parameters Optimization by Using Genetic Algorithm. Andri Mirzal, Shinichiro Yoshii, Masashi Furukawa

DISCRETE TIME FOURIER TRANSFORM (DTFT)

Lecture 2: Current in RC circuit D.K.Pandey

Math 266, Practice Midterm Exam 2

PERIODICAL SOLUTION OF SOME DIFFERENTIAL EQUATIONS UDC 517.9(045)=20. Julka Knežević-Miljanović

1 Finite Automata and Regular Expressions

Chapter 3: Fourier Representation of Signals and LTI Systems. Chih-Wei Liu

SECTION where P (cos θ, sin θ) and Q(cos θ, sin θ) are polynomials in cos θ and sin θ, provided Q is never equal to zero.

CPSC 211 Data Structures & Implementations (c) Texas A&M University [ 259] B-Trees

= x. I (x,y ) Example: Translation. Operations depend on pixel s Coordinates. Context free. Independent of pixel values. I(x,y) Forward mapping:

Lecture 1: Growth and decay of current in RL circuit. Growth of current in LR Circuit. D.K.Pandey

whereby we can express the phase by any one of the formulas cos ( 3 whereby we can express the phase by any one of the formulas

Charging of capacitor through inductor and resistor

Advanced Engineering Mathematics, K.A. Stroud, Dexter J. Booth Engineering Mathematics, H.K. Dass Higher Engineering Mathematics, Dr. B.S.

Decline Curves. Exponential decline (constant fractional decline) Harmonic decline, and Hyperbolic decline.

Continous system: differential equations

Nikesh Bajaj. Fourier Analysis and Synthesis Tool. Guess.? Question??? History. Fourier Series. Fourier. Nikesh Bajaj

2.1. Differential Equations and Solutions #3, 4, 17, 20, 24, 35

Mathcad Lecture #4 In-class Worksheet Vectors and Matrices 1 (Basics)

(1) Then we could wave our hands over this and it would become:

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS

Note 6 Frequency Response

On the Derivatives of Bessel and Modified Bessel Functions with Respect to the Order and the Argument

EE 224 Signals and Systems I Complex numbers sinusodal signals Complex exponentials e jωt phasor addition

EE 350 Signals and Systems Spring 2005 Sample Exam #2 - Solutions

3+<6,&6([DP. September 29, SID (last 5 digits): --

A THREE COMPARTMENT MATHEMATICAL MODEL OF LIVER

B) 25y e. 5. Find the second partial f. 6. Find the second partials (including the mixed partials) of

XV Exponential and Logarithmic Functions

Chapter 7: Inverse-Response Systems

Spectral Synthesis in the Heisenberg Group

Circuit Transients time

Applied Statistics and Probability for Engineers, 6 th edition October 17, 2016

Jonathan Turner Exam 2-12/4/03

The Matrix Exponential

Digital Image Processing

Effect of sampling on frequency domain analysis

The Matrix Exponential

NEW APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA

Feedback Control and Synchronization of Chaos for the Coupled Dynamos Dynamical System *

Wave Equation (2 Week)

Introduction to Fourier Transform

General Article Application of differential equation in L-R and C-R circuit analysis by classical method. Abstract

Master Thesis Seminar

Homework #2: CMPT-379 Distributed on Oct 2; due on Oct 16 Anoop Sarkar

ECE Connections: What do Roots of Unity have to do with OP-AMPs? Louis Scharf, Colorado State University PART 1: Why Complex?

Discussion 06 Solutions

10. The Discrete-Time Fourier Transform (DTFT)

Combinatorial Networks Week 1, March 11-12

LESSON 10: THE LAPLACE TRANSFORM

[ ] [ ] DFT: Discrete Fourier Transform ( ) ( ) ( ) ( ) Congruence (Integer modulo m) N-point signal

EXERCISE - 01 CHECK YOUR GRASP

Lecture 13 RC/RL Circuits, Time Dependent Op Amp Circuits

Math 3301 Homework Set 6 Solutions 10 Points. = +. The guess for the particular P ( ) ( ) ( ) ( ) ( ) ( ) ( ) cos 2 t : 4D= 2

Circuits and Systems I

Consider a system of 2 simultaneous first order linear equations

Transcription:

THE LAPLACE TRANSFORM LEARNING GOALS Diniion Th ranorm map a ncion o im ino a ncion o a complx variabl Two imporan inglariy ncion Th ni p and h ni impl Tranorm pair Baic abl wih commonly d ranorm Propri o h ranorm Thorm dcribing propri. Many o hm ar l a compaional ool Prorming h invr ranormaion By rricing anion o raional ncion on can impliy h invrion proc Convolion ingral Baic rl in ym analyi Iniial and Final val horm Ul rl rlaing im and -domain bhavior

ONE-SIDED LAPLACE TRANSFORM I will b ncary o conidr To inr niqn o h h ingral RoC σ jω a h ranorm on i lowr limi am wll dind or < A SUFFICIENT CONDITION FOR EXISTENCE OF LAPLACE TRANSFORM Tranorm xi or R{} σ > THE INVERSE TRANSFORM Conor ingral in h complx plan Evalaing h ingral can b qi im-conming. For hi raon w dvlop br procdr ha apply only o crain l cla o ncion

TWO SINGULARITY FUNCTIONS Uni p Imporan ncion in ym analyi Thi ncion ha drivaiv ha i zro vrywhr xcp a h origin. W will din a drivaiv or i For poiiv im ncion Uing qar pl o approxima an arbirary ncion Th narrowr h pl h br h approximaion Uing h ni p o bild ncion

Comping h ranorm o h ni p U T x x dx limt T x lim T U dx An xampl o Rgion o Convrgnc RoC Im T U limt σ jω U lim T σt jωt σ jω U ; R{ } > To impliy qion o RoC: A pcial cla o ncion RoC { : R{ } RoC }> σ In hi ca h RoC i a la hal a plan. And any linar combinaion o ch ignal will alo hav a RoC ha i a hal plan R{ } > Complx Plan R

THE IMPULSE FUNCTION Good modl or impac, lighning, and ohr wll known phnomna Th wo condiion ar no aibl or normal ncion Approximaion o h impl High i proporional o ara Rprnaion o h impl Siing or ampling propry o h impl Laplac ranorm For or h ingral i NOT dind In ordr o hav a valid ranorm or δ lowr limi i amd h

LEARNING BY DOING < π < π coπ π π > LEARNING EXAMPLE d Ingraion by par, dv d wih d d, v W will dvlop propri ha will prmi h drminaion o a larg nmbr o ranorm rom a mall abl o ranorm pair

Linariy Tim hiing Tim rncaion Mliplicaion by xponnial Mliplicaion by im Som propri will b provd and d a icin ool in h compaion o Laplac ranorm

LEARNING EXAMPLE Find h ranorm or F a d F a a a d a LINEARITY PROPERTY Homogniy Follow immdialy rom h linariy propri o h ingral APPLICATION Addiiviy Baic Tabl o Laplac Tranorm a jω jω jω L [ ] L[ ] a jω W dvlop propri ha xpand h abl and allow compaion o ranorm wiho ing h diniion F jω jω jω jω jω jω ω

Wih a imilar o linariy on how L[inω] ω ω Addiional nri or h abl LEARNING EXAMPLE Applicaion o Linariy X 4 4 LEARNING EXAMPLE Find h Laplac ranorm or x co π / x coπ /co in π /in Noic ha h ni p i no hown xplicily. Hnc and ar qivaln X coπ / in π / 9 9

MULTIPLICATION BY EXPONENTIAL LEARNING EXAMPLE a a L[ y ] y d y d a LEARNING EXAMPLE co Y a a X coπ /co4 in π /in 4 x a, b 4 coπ / in π 6 4 / 6 y co Y From abl y F Y Nw nri or h abl o ranorm pair

MULTIPLICATION BY TIME Dirniaion ndr an ingral Rmmbr ha w conidr h o b zro or x x <. Hnc ncion LEARNING EXAMPLE Find h r U o ranorm o d d n! n n L b h ni h ramp ncion d d By cciv applicaion h propry on how Thi rl, pl linariy, allow compaion o h ranorm o any polynomial LEARNING BY DOING x 6! X 4 p

TIME SHIFTING PROPERTY F F LEARNING EXAMPLE lwhr F

LEARNING EXTENSION FIND THE TRANSFORM FOR On can apply h im hiing propry i h im variabl alway appar a i appar in h argmn o h p. In hi ca a - On cold alo wri g And apply h im rncaion propry L g F [ g ] g L[ g ] Th wo propri ar only dirn rprnaion o h am rl

LEARNING EXAMPLE 6 6 F /6 in x π LEARNING EXAMPLE /6 in x π in 6 / 4 x θ π θ co in in co x θ θ 4 in 4 in 4 co 4 co 4 in 4 co X θ θ Uing im rncaion ] [ g F g L g g 6 ] [ 6 g L g ] [ g X L

A LEARNING EXTENSION Comp h Laplac ranorm o h ollowing ncion 4 4 5 4 5 4x 4 x B g G L[ ] a 4 a 4 4 x G a 4 C x co b X L[co b ] co b co bco b in bin b L[co b ] cob in b b b b X cob in b b b b

LEARNING EXTENSION lwhr 4 Comp h Laplac ranorm 4 4 4 4 4 4 4 4 F 4 4 4 4 d F diniion h Uing

PERFORMING THE INVERSE TRANSFORM Simpl, complx conjga pol FACT: Mo o h Laplac ranorm ha w nconr ar propr raional ncion o h orm Zro roo o nmraor Pol roo o dnominaor o m n NOWN: PARTIAL FRACTION EXPANSION I Q Q Q i a COPRIME acorizaion h dg Q n F i dnominaor wih i n P P ; Q Q i n, hn I m<n and h pol ar impl dg P < n i i C α α β Pol wih mlipliciy r Cβ α β... THE INVERSE TRANSFORM OF EACH PARTIAL FRACTION IS IMMEDIATE. WE ONLY NEED TO COMPUTE THE VARIOUS CONSTANTS

SIMPLE POLES / pi LEARNING EXAMPLE F 4 5 Wri h parial racion xpanion 4 F 4 5 Drmin h coicin rid 9 F 4 5 F 4 F 4 4 4 5 F 5 5 6 8 4 5 G h invr o ach rm and wri h inal anwr 9 6 8 4 5 5 Th p ncion i ncary o mak h ncion zro or < FORM o h invr ranorm 4 5 4

LEARNING EXTENSIONS 6 A F Find h invr ranorm Parial racion. Parial racion. Rid. Invr o ach rm F rid B F F F 6 6 F Formo olion : Invr o ach rm 5 5 4 Mak h ncion zro or <

COMPLEX CONJUGATE POLES θ α co β θ... USING QUADRATIC FACTORS Elr' coφ Idniy jφ jφ Q P [ α β ] C α α β Cβ α β... α α C co β C in β... Th wo orm ar qivaln! Avoid ing complx algbra. M drmin h coicin in dirn way

LEARNING EXAMPLE Y 4 5 Y 4 5 j j j j j * Y 4 j j 5 j 5 j Y j j j 5 5. 4 y 4.6co.678 Uing qadraic acor C C C Y 4 5 C j.6 5. 4 C 4 5.6 C C C C Alrnaiv way o drmin coicin : C For : 5C C C C 4 For : C C : 4C C C C For : C C C : 5C C 4 y C C co C in α co β θ... MUST radian in xponn.678 j

MULTIPLE POLES - L p n n! n / p p r Th mhod o idniicaion o coicin, or vn h mhod o lcing val o, may provid a convnin alrnaiv or h drminaion o h rid LEARNING EXAMPLE F 5 F 5 5 5 5 5 5 5 F 5 5 5 : For 4 d F : 5 5 5 r, j d : 5 For m dirnia 5 : 4 5 on mor im 5

LEARNING EXAMPLE F F d d F d d!! d d F d d 4 : 4 : 5 : : F Uing idniicaion o coicin

LEARNING EXTENSION Find h invr ranorm F Parial racion F Form o h invr Rid F alrnaivly F d F d

LEARNING EXTENSION Find h invr ranorm F Parial racion xpanion F Form o h invr Rid F F F d d F invr d d

CONVOLUTION INTEGRAL zro a rpon h Acally, or qaion h o olion a pariclar i ch ha, a ncion, hr xi Givn an ODE CLAIM:,...... h dx x x h y h b d d b y a d y d a d y d m m m n n n n n PROOF Shiing ncion im poiiv ar,, : I RESULT F F F ; > dx x y y Y x FIND EXAMPLE y y Y Y Y Y

LEARNING EXAMPLE Uing convolion o drmin a nwork rpon Nwork V H V S ncion V 5 5 5 5 Inp V S 5 v 5 λ 5 dλ v V S H V V H VS RESULT :I,, ar poiiv im ncion dλ 5λ 5 5 v [ ] ; For 5 5 λ F F F In gnral convolion i no an icin approach o drmin h op o a ym. B i can b a vry l ool in pcial ca

LEARNING EXAMPLE Thi xampl illra an idalizd modling approach and h o convolion a a ym imlaion ool. Thi lid how how on can obain a black box modl or a ym V in V o H Unknown linar ym rprnd in h Laplac domain Idal approach o modling Mar h impl rpon v o h x v in x dx v in V For any ohr inp on ha δ V o H V H, v In pracic, a good approximaion o an impl may b diicl, or impoibl o apply. Hnc w ry o mor nibl inp. in in o, h Th black box modl i a dcripion o h ym bad only on inp/op daa. Thr i no inormaion on wha i inid h box v in Uing h p rpon H Vin, Vo d H Vo h vo d Th impl rpon i h drivaiv o h p rpon o a ym Onc h impl rpon i obaind, h convolion can b valad nmrically

A CASE STUDY IN MODELING Unknown ym p rpon Compd impl rpon ini dirnc approximaion o drivaiv

T o h modl Th modl op h compd impl rpon and ampl o h inp ignal. Convolion ingral i valad nmrically y kt kt h kt x x dx k j h k j jt T

Daild viw o a gmn o h ignal howing bandpa acion DC and high rqncy ar rdcd in h op y kt kt h kt x x dx k j h k j jt T

INITIAL AND FINAL VALUE THEOREMS Th rl rla bhavior o a ncion in h im domain wih h bhavior o h Laplac ranorm in h -domain INITIAL VALUE THEOREM Am ha boh, d ranorm. Thn lim lim F, hav Laplac d d L[ ] F d And i h drivaiv i lim d L[ d ] ranormabl hn lim FINAL VALUE THEOREM Am ha boh, d ranorm and ha NOTE: lim lim lim F d, hav Laplac xi. Thn will xi i F ha pol wih ngaiv ralpar and a mo a ingl pol a d d d d d d F Taking limi a lim F

LEARNING EXAMPLE Givn F. Drmin h iniial and inal val or LEARNING EXTENSION Givn F. Drmin h iniial and inal val or Clarly, ha Laplac ranorm. And F - i alo dind. lim F lim lim F ha on pol a and h ohr hav ngaiv ral par. Th inal val horm can b applid. lim lim F lim lim 5 lim lim 4 NOTE:Comping h invr on 5 5 π co 4 g

On way o ing Laplac ranorm chniq in circi analyi h ollowing p:. Driv h dirnial qaion ha dcrib h nwork. Apply h ranorm a a ool o olv h dirnial qaion

LEARNING BY APPLICATION FIND i, > To ind h iniial condiion w h ady a ampion or < v R v L v S v v v v W will wri h qaion or i and olv i ing Laplac Tranorm For > S R L C, di L d v Ri C C v v v v S > R i x dx di i vc d C vc I I i L C On cold wri VL in h Laplac domain and kip h im domain i x dx I. L Circi in ady a or < V i 4 A; v C V 4 V Ω 4 4 I Rplac and rarrang 4 4 I j j * 4 I j j j j 4 j 4.6 7.57. 8. 4 j6 6 9 σ σ i co ω θ ω θ 8.4

LEARNING EXTENSION Aming h circi in ady a or drmin i, >. <, v R v L Eqaion or > 6 i di d Tranorming o h Laplac domain 6 I I i Nx w m drmin i Circi in ady a or < 6V i A Ω 6 I I I I i A; > Laplac