MA2327, Problem set #3 (Practice problems with solutions)

Similar documents
The Exponential of a Matrix

Linear algebra II Tutorial solutions #1 A = x 1

Section 4.3 version November 3, 2011 at 23:18 Exercises 2. The equation to be solved is

Linear algebra II Homework #1 solutions A = This means that every eigenvector with eigenvalue λ = 1 must have the form

Math Ordinary Differential Equations

Solutions Problem Set 8 Math 240, Fall

Find the general solution of the system y = Ay, where

Differential Equations 2280 Sample Midterm Exam 3 with Solutions Exam Date: 24 April 2015 at 12:50pm

Solutions to Homework 5, Introduction to Differential Equations, 3450: , Dr. Montero, Spring y 4y = 48t 3.

Linear algebra II Homework #1 due Thursday, Feb. 2 A =. 2 5 A = When writing up solutions, write legibly and coherently.

Differential Equations and Linear Algebra - Fall 2017

MATH 3321 Sample Questions for Exam 3. 3y y, C = Perform the indicated operations, if possible: (a) AC (b) AB (c) B + AC (d) CBA

Math 20D Final Exam 8 December has eigenvalues 3, 3, 0 and find the eigenvectors associated with 3. ( 2) det

UNIVERSITY OF OSLO. Please make sure that your copy of the problem set is complete before you attempt to answer anything.

Linear Algebra Practice Problems

Theory of Linear Systems Exercises. Luigi Palopoli and Daniele Fontanelli

1 Systems of Differential Equations

MathQuest: Differential Equations

Test #2 Math 2250 Summer 2003

MA Ordinary Differential Equations and Control Semester 1 Lecture Notes on ODEs and Laplace Transform (Parts I and II)

Systems of Linear Differential Equations Chapter 7

Math Matrix Algebra

1. What is the determinant of the following matrix? a 1 a 2 4a 3 2a 2 b 1 b 2 4b 3 2b c 1. = 4, then det

Applied Differential Equation. November 30, 2012

Linear algebra II Homework #1 due Thursday, Feb A =

Math 215 HW #9 Solutions

APPM 2360: Midterm exam 3 April 19, 2017

Section 9.8 Higher Order Linear Equations

Differential Equations Practice: 2nd Order Linear: Nonhomogeneous Equations: Undetermined Coefficients Page 1

Matrix Theory and Differential Equations Practice For the Final in BE1022 Thursday 14th December 2006 at 8.00am

Even-Numbered Homework Solutions

Ordinary Differential Equations. Raz Kupferman Institute of Mathematics The Hebrew University

Math 4B Notes. Written by Victoria Kala SH 6432u Office Hours: T 12:45 1:45pm Last updated 7/24/2016

Generalized Eigenvectors and Jordan Form

LINEAR EQUATIONS OF HIGHER ORDER. EXAMPLES. General framework

MATH 320 INHOMOGENEOUS LINEAR SYSTEMS OF DIFFERENTIAL EQUATIONS

Calculus for the Life Sciences II Assignment 6 solutions. f(x, y) = 3π 3 cos 2x + 2 sin 3y

Matrix Solutions to Linear Systems of ODEs

1. In this problem, if the statement is always true, circle T; otherwise, circle F.

FIRST-ORDER SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS II: Homogeneous Linear Systems with Constant Coefficients

Reduction to the associated homogeneous system via a particular solution

SYSTEMTEORI - ÖVNING 1. In this exercise, we will learn how to solve the following linear differential equation:

Math 304 Answers to Selected Problems

Homogeneous Linear Systems of Differential Equations with Constant Coefficients

1. Diagonalize the matrix A if possible, that is, find an invertible matrix P and a diagonal

June 2011 PURDUE UNIVERSITY Study Guide for the Credit Exam in (MA 262) Linear Algebra and Differential Equations

DIFFERENTIAL EQUATIONS REVIEW. Here are notes to special make-up discussion 35 on November 21, in case you couldn t make it.

Linear Differential Equations. Problems

This is a closed book exam. No notes or calculators are permitted. We will drop your lowest scoring question for you.

Math 315: Linear Algebra Solutions to Assignment 7

Additional Homework Problems

π 1 = tr(a), π n = ( 1) n det(a). In particular, when n = 2 one has

and let s calculate the image of some vectors under the transformation T.

+ i. cos(t) + 2 sin(t) + c 2.

MATH 5524 MATRIX THEORY Problem Set 5

Ma 227 Review for Systems of DEs

Periodic Linear Systems

Modeling and Simulation with ODE for MSE

Jordan normal form notes (version date: 11/21/07)

Eigenvalue and Eigenvector Homework

1. The Transition Matrix (Hint: Recall that the solution to the linear equation ẋ = Ax + Bu is

MATH 24 EXAM 3 SOLUTIONS

Math 240 Calculus III

= AΦ, Φ(0) = I, = k! tk A k = I + ta t2 A t3 A t4 A 4 +, (3) e ta 1

Symmetric and anti symmetric matrices

HANDOUT E.22 - EXAMPLES ON STABILITY ANALYSIS

Systems of Second Order Differential Equations Cayley-Hamilton-Ziebur

Section 9.3 Phase Plane Portraits (for Planar Systems)

6 Linear Equation. 6.1 Equation with constant coefficients

Third Midterm Exam Name: Practice Problems November 11, Find a basis for the subspace spanned by the following vectors.

APPM 2360 Section Exam 3 Wednesday November 19, 7:00pm 8:30pm, 2014

CAAM 335 Matrix Analysis

Jordan Canonical Form Homework Solutions

Lecture 6. Eigen-analysis

Sign the pledge. On my honor, I have neither given nor received unauthorized aid on this Exam : 11. a b c d e. 1. a b c d e. 2.

Jordan Canonical Form

Higher Order Linear Equations Lecture 7

State will have dimension 5. One possible choice is given by y and its derivatives up to y (4)

CHEE 319 Tutorial 3 Solutions. 1. Using partial fraction expansions, find the causal function f whose Laplace transform. F (s) F (s) = C 1 s + C 2

ES.1803 Topic 19 Notes Jeremy Orloff. 19 Variation of parameters; exponential inputs; Euler s method

MATH 251 Examination II April 7, 2014 FORM A. Name: Student Number: Section:

MATH 312 Section 8.3: Non-homogeneous Systems

= 2e t e 2t + ( e 2t )e 3t = 2e t e t = e t. Math 20D Final Review

Differential equations

Chapter 12: Iterative Methods

3. Identify and find the general solution of each of the following first order differential equations.

Ma 227 Final Exam Solutions 12/13/11

20D - Homework Assignment 4

MATH 251 Examination II April 4, 2016 FORM A. Name: Student Number: Section:

(a) II and III (b) I (c) I and III (d) I and II and III (e) None are true.

Homework 3 Solutions Math 309, Fall 2015

Eigenvalues, Eigenvectors, and Diagonalization

NOTES ON LINEAR NON-AUTONOMOUS SYSTEMS

THE USE OF A CALCULATOR, CELL PHONE, OR ANY OTHER ELEC- TRONIC DEVICE IS NOT PERMITTED DURING THIS EXAMINATION.

Poincaré Map, Floquet Theory, and Stability of Periodic Orbits

Practice Final Exam Solutions for Calculus II, Math 1502, December 5, 2013

Conceptual Questions for Review

MATH 215/255 Solutions to Additional Practice Problems April dy dt

Eigenvalues and Eigenvectors 7.1 Eigenvalues and Eigenvecto

SOLUTIONS TO PRACTICE EXAM 3, SPRING 2004

Transcription:

MA2327, Problem set #3 (Practice problems with solutions) 5 2 Compute the matrix exponential e ta in the case that A = 2 5 2 Compute the matrix exponential e ta in the case that A = 5 3 Find the unique solution of the initial value problem y (t) 3y (t)+4y(t) = 0, y(0) =, y (0) = 4, y (0) = 3 4 Use the matrix exponential to solve the initial value problem 6 3 y (t) = Ay(t), A =, y(0) = 2 3 5 Suppose that Φ(t) is a fundamental matrix for the system y (t) = A(t)y(t) Find the matrix A(t) and determine the unique solution that satisfies y(0) = y 0 when sint cost Φ(t) = e sint, y cost sint 0 = 0 6 Suppose that Φ(t) is a fundamental matrix for the system y (t) = Ay(t) Find the constant matrix A and compute its matrix exponential e ta when sint cost Φ(t) = cost sint Compute the matrix exponential e ta in the case that A = 5 2 2 The characteristic polynomial of the given matrix is f(λ) = λ 2 (tra)λ+deta = λ 2 6λ+9 = (λ 3) 2 Thus, λ = 3 is the only eigenvalue and it is easy to check that the only eigenvector is v =

Pick any nonzero vector v that is not an eigenvector and let v 2 = (A λi)v, say 2 v =, v 0 2 = (A 3I)v = 2 These vectors form a Jordan basis for A and we also have 2 3 e B = = J = B AB = = e tj 3t = 0 2 3 te 3t e 3t As for the exponential of the original matrix A, this is given by 2 +2t 2t e ta = Be tj B = e 3t = e 3t 0 2 t 0 /2 2t 2t 2 Compute the matrix exponential e ta in the case that A = The characteristic polynomial of the given matrix is 5 5 f(λ) = λ 2 (tra)λ+deta = λ 2 6λ+0 = (λ 3) 2 + Thus, the eigenvalues are λ = 3±i and the corresponding eigenvectors turn out to be v =, v 2 i 2 = 2+i This implies that A is diagonalisable and that we also have 3+i B = = J = B AB = 2 i 2+i 3 i e = e tj = 3t e it e 3t e it As for the exponential of the original matrix A, this is given by e e ta = Be tj B = e 3t it 2 i 2+i e it 2+i 2i i 2 = e3t (i+2)e it +(i 2)e it e it e it 2i 5e it 5e it (i 2)e it +(i+2)e it Using the formula e ±it = cost±isint, we may thus conclude that e ta = e3t 2icost+4isint 2isint 2i 0isint 2icost 4isint cost+2sint sint = e 3t 5sint cost 2sint

3 Find the unique solution of the initial value problem y (t) 3y (t)+4y(t) = 0, y(0) =, y (0) = 4, y (0) = 3 This is a homogeneous equation and the associated characteristic polynomial is λ 3 3λ 2 +4 = 0 Noting that λ = is a root, it is easy to check that λ 3 3λ 2 +4 = (λ+)(λ 2 4λ+4) = (λ+)(λ 2) 2 In particular, λ = 2 is a double root and λ = is a simple root, so y(t) = c e 2t +c 2 te 2t +c 3 e t for some constants c,c 2,c 3 Next, we turn to the initial conditions and we note that y(t) = c e 2t +c 2 te 2t +c 3 e t, y (t) = 2c e 2t +c 2 e 2t +2c 2 te 2t c 3 e t, y (t) = 4c e 2t +4c 2 e 2t +4c 2 te 2t +c 3 e t This gives rise to a system of three equations in three unknowns, namely = y(0) = c +c 3, 4 = y (0) = 2c +c 2 c 3, 3 = y (0) = 4c +4c 2 +c 3 On the other hand, row reduction of the associated augmented matrix gives 0 0 0 2 2 4 0 0 4 4 3 0 0 Thus, the unique solution of the system is (c,c 2,c 3 ) = (2,, ) and we finally get y(t) = c e 2t +c 2 te 2t +c 3 e t = 2e 2t te 2t e t 4 Use the matrix exponential to solve the initial value problem 6 3 y (t) = Ay(t), A =, y(0) = 2 3 The characteristic polynomial of the given matrix is f(λ) = λ 2 (tra)λ+deta = λ 2 8λ+5 = (λ 5)(λ 3)

Since the eigenvalues are distinct, A is diagonalisable, and it is easy to check that 3 v =, v 2 = are eigenvectors corresponding to λ = 5 and λ = 3, respectively This implies that 3 5 e B = = J = B AB = = e tj 5t = 3 e 3t In particular, the matrix exponential of the original matrix A is given by e ta = Be tj B = 3 e 5t 2 e 3t 3 = 3e 5t e 3t 3e 3t 3e 5t 2 e 5t e 3t 3e 3t e 5t Next, we turn to the initial value problem Since Φ(t) = e ta is a fundamental matrix, every solution has the form y(t) = Φ(t)c = e ta c for some vector c and this implies that y(0) = e 0 c = c = y(t) = e ta y(0) = y(t) = 3e 5t e 3t 3e 3t 3e 5t 2 e 5t e 3t 3e 3t e 5t = 3 [ 4e 3t 3e 5t 4e 3t e 5t ] 5 Suppose that Φ(t) is a fundamental matrix for the system y (t) = A(t)y(t) Find the matrix A(t) and determine the unique solution that satisfies y(0) = y 0 when sint cost Φ(t) = e sint, y cost sint 0 = 0 The fundamental matrix is itself a matrix solution of the system, so one has Φ (t) = A(t)Φ(t) = A(t) = Φ (t) Φ(t) When it comes to the derivative Φ (t), an application of the product rule gives sint cost cost sint Φ (t) = e sint cost +e sint cost sint sint cost On the other hand, the inverse of Φ(t) is easily seen to be sint cost Φ(t) = e sint cost sint

Once we now combine the last three equations, we find that sint cost sint cost cost sint sint cost A(t) = cost + cost sint cost sint sint cost cost sint Using this fact together with the identity sin 2 t+cos 2 t =, we conclude that 0 0 cost A(t) = cost + = 0 0 cost Next, we turn to the initial value problem Since Φ(t) is a fundamental matrix, we have y(t) = Φ(t)c = y(0) = Φ(0)c = c = Φ(0) y(0) = y(t) = Φ(t)Φ(0) y(0) Since y(0) = e by assumption, the unique solution of the problem is thus sint cost 0 y(t) = e sint cost sint 0 0 sint cost 0 cost = e sint = e sint cost sint 0 0 sint 6 Suppose that Φ(t) is a fundamental matrix for the system y (t) = Ay(t) Find the constant matrix A and compute its matrix exponential e ta when sint cost Φ(t) = cost sint The fundamental matrix is itself a matrix solution of the system, so one has Φ (t) = AΦ(t) = A = Φ (t) Φ(t) Using the given formula for Φ(t), it is thus easy to check that cost sint sint cost 0 A = = sint cost cost sint 0 To compute the matrix exponential e ta, one may now proceed in the usual way to find the eigenvalues and eigenvectors of A However, it is also possible to compute e ta by relating it to the fundamental matrix Φ(t) as follows Consider the initial value problem y (t) = Ay(t), y(0) = y 0

Since the unique solution can be expressed in the form y(t) = Φ(t)c, we have y(0) = Φ(0)c = c = Φ(0) y(0) = y(t) = Φ(t)c = Φ(t)Φ(0) y(0) On the other hand, e ta is itself a fundamental matrix, so the solution is also given by y(t) = e ta c = y(0) = c = y(t) = e ta c = e ta y(0) These two expressions must obviously coincide for any y(0) by uniqueness, hence ] [ sint cost 0 e ta = Φ(t)Φ(0) = cost sint 0 sint cost 0 cost sint = = cost sint 0 sint cost