# Notes On Diffy Qs: Differential Equations For Engineers

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Notes on Diffy QsDifferential Equations for Engineersby Jiří LeblJuly 21, 2020(version 6.1)

ContentsIntroduction70.1 Notes about these notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70.2 Introduction to differential equations . . . . . . . . . . . . . . . . . . . . . . . 100.3 Classification of differential equations . . . . . . . . . . . . . . . . . . . . . . 17123First order equations1.1 Integrals as solutions . . . . . . . . . . . . .1.2 Slope fields . . . . . . . . . . . . . . . . . . .1.3 Separable equations . . . . . . . . . . . . . .1.4 Linear equations and the integrating factor1.5 Substitution . . . . . . . . . . . . . . . . . .1.6 Autonomous equations . . . . . . . . . . . .1.7 Numerical methods: Euler’s method . . . .1.8 Exact equations . . . . . . . . . . . . . . . .1.9 First order linear PDE . . . . . . . . . . . . .Higher order linear ODEs2.1 Second order linear ODEs . . . . . . . . . . . .2.2 Constant coefficient second order linear ODEs2.3 Higher order linear ODEs . . . . . . . . . . . .2.4 Mechanical vibrations . . . . . . . . . . . . . .2.5 Nonhomogeneous equations . . . . . . . . . . .2.6 Forced oscillations and resonance . . . . . . . .Systems of ODEs3.1 Introduction to systems of ODEs . . . . . . . . .3.2 Matrices and linear systems . . . . . . . . . . . .3.3 Linear systems of ODEs . . . . . . . . . . . . . .3.4 Eigenvalue method . . . . . . . . . . . . . . . . .3.5 Two-dimensional systems and their vector fields3.6 Second order systems and applications . . . . . .3.7 Multiple eigenvalues . . . . . . . . . . . . . . . .3.8 Matrix exponentials . . . . . . . . . . . . . . . . .3.9 Nonhomogeneous systems . . . . . . . . . . . . 6140147152162169177

44CONTENTSFourier series and PDEs4.1 Boundary value problems . . . . . . . . . . . . . . . .4.2 The trigonometric series . . . . . . . . . . . . . . . . .4.3 More on the Fourier series . . . . . . . . . . . . . . . .4.4 Sine and cosine series . . . . . . . . . . . . . . . . . . .4.5 Applications of Fourier series . . . . . . . . . . . . . .4.6 PDEs, separation of variables, and the heat equation .4.7 One-dimensional wave equation . . . . . . . . . . . .4.8 D’Alembert solution of the wave equation . . . . . . .4.9 Steady state temperature and the Laplacian . . . . . .4.10 Dirichlet problem in the circle and the Poisson kernel.1891891982082182262322432522582645More on eigenvalue problems5.1 Sturm–Liouville problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5.2 Higher order eigenvalue problems . . . . . . . . . . . . . . . . . . . . . . . .5.3 Steady periodic solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2732732822866The Laplace transform6.1 The Laplace transform . . . . . . . . . . .6.2 Transforms of derivatives and ODEs . . .6.3 Convolution . . . . . . . . . . . . . . . . .6.4 Dirac delta and impulse response . . . . .6.5 Solving PDEs with the Laplace transform.2932933003083133207Power series methods7.1 Power series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7.2 Series solutions of linear second order ODEs . . . . . . . . . . . . . . . . . .7.3 Singular points and the method of Frobenius . . . . . . . . . . . . . . . . . .3273273353428Nonlinear systems8.1 Linearization, critical points, and equilibria . . . . .8.2 Stability and classification of isolated critical points8.3 Applications of nonlinear systems . . . . . . . . . .8.4 Limit cycles . . . . . . . . . . . . . . . . . . . . . . .8.5 Chaos . . . . . . . . . . . . . . . . . . . . . . . . . . .351351357364373378.385385396407421428436A Linear algebraA.1 Vectors, mappings, and matrices . . .A.2 Matrix algebra . . . . . . . . . . . . . .A.3 Elimination . . . . . . . . . . . . . . . .A.4 Subspaces, dimension, and the kernelA.5 Inner product and projections . . . . .A.6 Determinant . . . . . . . . . . . . . . .

CONTENTS5B Table of Laplace Transforms443Further Reading445Solutions to Selected Exercises447Index461

6CONTENTS

Introduction0.1Notes about these notesNote: A section for the instructor.This book originated from my class notes for Math 286 at the University of Illinois atUrbana-Champaign (UIUC) in Fall 2008 and Spring 2009. It is a first course on differentialequations for engineers. Using this book, I also taught Math 285 at UIUC, Math 20D atUniversity of California, San Diego (UCSD), and Math 4233 at Oklahoma State University(OSU). Normally these courses are taught with Edwards and Penney, Differential Equationsand Boundary Value Problems: Computing and Modeling [EP], or Boyce and DiPrima’sElementary Differential Equations and Boundary Value Problems [BD], and this book aims tobe more or less a drop-in replacement. Other books I used as sources of informationand inspiration are E.L. Ince’s classic (and inexpensive) Ordinary Differential Equations [I],Stanley Farlow’s Differential Equations and Their Applications [F], now available from Dover,Berg and McGregor’s Elementary Partial Differential Equations [BM], and William Trench’sfree book Elementary Differential Equations with Boundary Value Problems [T]. See the FurtherReading chapter at the end of the book.0.1.1OrganizationThe organization of this book to some degree requires chapters be done in order. Laterchapters can be dropped. The dependence of the material covered is roughly:IntroductionAppendix AChapter 1Chapter 2Chapter 3Chapter 8Chapter 7Chapter 4Chapter 5Chapter 6

8INTRODUCTIONThere are a few references in chapters 4 and 5 to chapter 3 (some linear algebra), butthese references are not essential and can be skimmed over, so chapter 3 can safely bedropped, while still covering chapters 4 and 5. Chapter 6 does not depend on chapter 4except that the PDE section 6.5 makes a few references to chapter 4, although it could, intheory, be covered separately. The more in-depth appendix A on linear algebra can replacethe short review § 3.2 for a course that combines linear algebra and ODE.0.1.2Typical types of coursesSeveral typical types of courses can be run with the book. There are the two originalcourses at UIUC, both cover ODE as well some PDE. Either, there is the 4 hours-a-week fora semester (Math 286 at UIUC):Introduction (0.2), chapter 1 (1.1–1.7), chapter 2, chapter 3, chapter 4 (4.1–4.9), chapter 5 (or6 or 7 or 8).Or, the second course at UIUC is at 3 hours-a-week (Math 285 at UIUC):Introduction (0.2), chapter 1 (1.1–1.7), chapter 2, chapter 4 (4.1–4.9), (and maybe chapter 5,6, or 7).A semester-long course at 3 hours a week that doesn’t cover either systems or PDEwill cover, beyond the introduction, chapter 1, chapter 2, chapter 6, and chapter 7, (withsections skipped as above). On the other hand, a typical course that covers systems willprobably need to skip Laplace and power series and cover chapter 1, chapter 2, chapter 3,and chapter 8.If sections need to be skipped in the beginning, a good core of the sections on singleODE is: 0.2, 1.1–1.4, 1.6, 2.1, 2.2, 2.4–2.6.The complete book can be covered at a reasonably fast pace at approximately 76lectures (without appendix A) or 86 lectures (with appendix A replacing § 3.2). This isnot accounting for exams, review, or time spent in a computer lab. A two-quarter or atwo-semester course can be easily run with the material. For example (with some sectionsperhaps strategically skipped):Semester 1: Introduction, chapter 1, chapter 2, chapter 6, chapter 7.Semester 2: Chapter 3, chapter 8, chapter 4, chapter 5.A combined course on ODE with linear algebra can run as:Introduction, chapter 1 (1.1–1.7), chapter 2, appendix A, chapter 3 (w/o § 3.2), (possiblychapter 8).The chapter on the Laplace transform (chapter 6), the chapter on Sturm–Liouville(chapter 5), the chapter on power series (chapter 7), and the chapter on nonlinear systems(chapter 8), are more or less interchangeable and can be treated as “topics”. If chapter 8is covered, it may be best to place it right after chapter 3, and chapter 5 is best coveredright after chapter 4. If time is short, the first two sections of chapter 7 make a reasonableself-contained unit.

0.1. NOTES ABOUT THESE NOTES0.1.39Computer resourcesThe book’s website https://www.jirka.org/diffyqs/ contains the following resources:1. Interactive SAGE demos.2. Online WeBWorK homeworks (using either your own WeBWorK installation orEdfinity) for most sections, customized for this book.3. The PDFs of the figures used in this book.I taught the UIUC courses using IODE (https://faculty.math.illinois.edu/iode/).IODE is a free software package that works with Matlab (proprietary) or Octave (freesoftware). The graphs in the book were made with the Genius software (see https://www.jirka.org/genius.html). I use Genius in class to show these (and other) graphs.The LATEX source of the book is also available for possible modification and customizationat github edgmentsFirstly, I would like to acknowledge Rick Laugesen. I used his handwritten class notesthe first time I taught Math 286. My organization of this book through chapter 5, andthe choice of material covered, is heavily influenced by his notes. Many examples andcomputations are taken from his notes. I am also heavily indebted to Rick for all the advicehe has given me, not just on teaching Math 286. For spotting errors and other suggestions,I would also like to acknowledge (in no particular order): John P. D’Angelo, Sean Raleigh,Jessica Robinson, Michael Angelini, Leonardo Gomes, Jeff Winegar, Ian Simon, ThomasWicklund, Eliot Brenner, Sean Robinson, Jannett Susberry, Dana Al-Quadi, Cesar Alvarez,Cem Bagdatlioglu, Nathan Wong, Alison Shive, Shawn White, Wing Yip Ho, Joanne Shin,Gladys Cruz, Jonathan Gomez, Janelle Louie, Navid Froutan, Grace Victorine, Paul Pearson,Jared Teague, Ziad Adwan, Martin Weilandt, Sönmez Şahutoğlu, Pete Peterson, ThomasGresham, Prentiss Hyde, Jai Welch, Simon Tse, Andrew Browning, James Choi, DustyGrundmeier, John Marriott, Jim Kruidenier, Barry Conrad, Wesley Snider, Colton Koop,Sarah Morse, Erik Boczko, Asif Shakeel, Chris Peterson, Nicholas Hu, Paul Seeburger,Jonathan McCormick, David Leep, William Meisel, Shishir Agrawal, Tom Wan, AndresValloud, and probably others I have forgotten. Finally, I would like to acknowledge NSFgrants DMS-0900885 and DMS-1362337.

100.2INTRODUCTIONIntroduction to differential equationsNote: more than 1 lecture, §1.1 in [EP], chapter 1 in [BD]0.2.1Differential equationsThe laws of physics are generally written down as differential equations. Therefore, allof science and engineering use differential equations to some degree. Understandingdifferential equations is essential to understanding almost anything you will study in yourscience and engineering classes. You can think of mathematics as the language of science,and differential equations are one of the most important parts of this language as far asscience and engineering are concerned. As an analogy, suppose all your classes from nowon were given in Swahili. It would be important to first learn Swahili, or you would have avery tough time getting a good grade in your classes.You saw many differential equations already without perhaps knowing about it. Andyou even solved simple differential equations when you took calculus. Let us see anexample you may not have seen:𝑑𝑥 𝑥 2 cos 𝑡.(1)𝑑𝑡Here 𝑥 is the dependent variable and 𝑡 is the independent variable. Equation (1) is a basicexample of a differential equation. It is an example of a first order differential equation, sinceit involves only the first derivative of the dependent variable. This equation arises fromNewton’s law of cooling where the ambient temperature oscillates with time.0.2.2Solutions of differential equationsSolving the differential equation means finding 𝑥 in terms of 𝑡. That is, we want to find afunction of 𝑡, which we call 𝑥, such that when we plug 𝑥, 𝑡, and 𝑑𝑥𝑑𝑡 into (1), the equationholds; that is, the left hand side equals the right hand side. It is the same idea as it wouldbe for a normal (algebraic) equation of just 𝑥 and 𝑡. We claim that𝑥 𝑥(𝑡) cos 𝑡 sin 𝑡is a solution. How do we check? We simply plug 𝑥 into equation (1)! First we need to𝑑𝑥compute 𝑑𝑥𝑑𝑡 . We find that 𝑑𝑡 sin 𝑡 cos 𝑡. Now let us compute the left-hand side of (1).𝑑𝑥 𝑥 ( sin 𝑡 cos 𝑡) (cos 𝑡 sin 𝑡) 2 cos 𝑡.𝑑𝑡 {z} {z }𝑑𝑥𝑑𝑡𝑥Yay! We got precisely the right-hand side. But there is more! We claim 𝑥 cos 𝑡 sin 𝑡 𝑒 𝑡is also a solution. Let us try,𝑑𝑥 sin 𝑡 cos 𝑡 𝑒 𝑡 .𝑑𝑡

110.2. INTRODUCTION TO DIFFERENTIAL EQUATIONSWe plug into the left-hand side of (1)𝑑𝑥 𝑥 ( sin 𝑡 cos 𝑡 𝑒 𝑡 ) (cos 𝑡 sin 𝑡 𝑒 𝑡 ) 2 cos 𝑡.𝑑𝑡{z} {z} 𝑥𝑑𝑥𝑑𝑡And it works yet again!So there can be many different solutions. For this equation all solutions can be writtenin the form𝑥 cos 𝑡 sin 𝑡 𝐶𝑒 𝑡 ,for some constant 𝐶. Different constants 𝐶 will give different solutions, so there are reallyinfinitely many possible solutions. See Figure 1 for the graph of a few of these solutions.We will see how we find these solutions a few lectures from now.Solving differential equations can bequite hard. There is no general methodthat solves every differential equation. Wewill generally focus on how to get exact formulas for solutions of certain differentialequations, but we will also spend a littlebit of time on getting approximate solutions. And we will spend some time onunderstanding the equations without solving them.Most of this book is dedicated to ordinarydifferential equations or ODEs, that is, equations with only one independent variable,Figure 1: Few solutions of 𝑑𝑥𝑑𝑡 𝑥 2 cos 𝑡.where derivatives are only with respect tothis one variable. If there are several independent variables, we get partial differentialequations or PDEs.Even for ODEs, which are very well understood, it is not a simple question of turninga crank to get answers. When you can find exact solutions, they are usually preferableto approximate solutions. It is important to understand how such solutions are found.Although in real applications you will leave much of the actual calculations to computers,you need to understand what they are doing. It is often necessary to simplify or transformyour equations into something that a computer can understand and solve. You may evenneed to make certain assumptions and changes in your model to achieve this.To be a successful engineer or scientist, you will be required to solve problems in yourjob that you never saw before. It is important to learn problem solving techniques, so thatyou may apply those techniques to new problems. A common mistake is to expect to learnsome prescription for solving all the problems you will encounter in your later career. Thiscourse is no exception.01234533221100-1-1012345

120.2.3INTRODUCTIONDifferential equations in practiceSo how do we use differential equations inReal-world problemscience and engineering? First, we have somereal-world problem we wish to understand. Weabstractinterpretmake some simplifying assumptions and cresolveate a mathematical model. That is, we translate MathematicalMathematicalthe real-world situation into a set of differentialmodelsolutionequations. Then we apply mathematics to getsome sort of a mathematical solution. There is still something left to do. We have to interpretthe results. We have to figure out what the mathematical solution says about the real-worldproblem we started with.Learning how to formulate the mathematical model and how to interpret the results iswhat your physics and engineering classes do. In this course, we will focus mostly on themathematical analysis. Sometimes we will work with simple real-world examples so thatwe have some intuition and motivation about what we are doing.Let us look at an example of this process. One of the most basic differential equations isthe standard exponential growth model. Let 𝑃 denote the population of some bacteria ona Petri dish. We assume that there is enough food and enough space. Then the rate ofgrowth of bacteria is proportional to the population—a large population grows quicker.Let 𝑡 denote time (say in seconds) and 𝑃 the population. Our model is𝑑𝑃 𝑘𝑃,𝑑𝑡for some positive constant 𝑘 0.Example 0.2.1: Suppose there are 100 bacteria at time 0 and 200 bacteria 10 seconds later.How many bacteria will there be 1 minute from time 0 (in 60 seconds)?First we need to solve the equation. Weclaim that a solution is given 0200010001000𝑘𝑡𝑃(𝑡) 𝐶𝑒 ,where 𝐶 is a constant. Let us try:𝑑𝑃 𝐶 𝑘𝑒 𝑘𝑡 𝑘𝑃.𝑑𝑡And it really is a solution.OK, now what? We do not know 𝐶, andwe do not know 𝑘. But we know something.We know 𝑃(0) 100, and we know 𝑃(10) 200. Let us plug these conditions in and seewhat happens.000102030405060Figure 2: Bacteria growth in the first 60 seconds.100 𝑃(0) 𝐶𝑒 𝑘0 𝐶,200 𝑃(10) 100 𝑒 𝑘10 .

0.2. INTRODUCTION TO DIFFERENTIAL EQUATIONSTherefore, 2 𝑒 10𝑘 orln 21013 𝑘 0.069. So𝑃(𝑡) 100 𝑒 (ln 2)𝑡/10 100 𝑒 0.069𝑡 .At one minute, 𝑡 60, the population is 𝑃(60) 6400. See Figure 2 on the preceding page.Let us talk about the interpretation of the results. Does our solution mean that theremust be exactly 6400 bacteria on the plate at 60s? No! We made assumptions that mightnot be true exactly, just approximately. If our assumptions are reasonable, then therewill be approximately 6400 bacteria. Also, in real life 𝑃 is a discrete quantity, not a realnumber. However, our model has no problem saying that for example at 61 seconds,𝑃(61) 6859.35.Normally, the 𝑘 in 𝑃 0 𝑘𝑃 is known, and we want to solve the equation for differentinitial conditions. What does that mean? Take 𝑘 1 fo

10 INTRODUCTION 0.2Introductiontodiﬀerentialequations .1Diﬀerentialequations .

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