8.2. Solution by Inverse Matrix Method. Introduction. Prerequisites. Learning Outcomes



Similar documents
Solving simultaneous equations using the inverse matrix

Equations, Inequalities & Partial Fractions

8.1. Cramer s Rule for Solving Simultaneous Linear Equations. Introduction. Prerequisites. Learning Outcomes. Learning Style

3.1. Solving linear equations. Introduction. Prerequisites. Learning Outcomes. Learning Style

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS

3.6. Partial Fractions. Introduction. Prerequisites. Learning Outcomes

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m

5.5. Solving linear systems by the elimination method

Solving Systems of Linear Equations Using Matrices

Question 2: How do you solve a matrix equation using the matrix inverse?

a 11 x 1 + a 12 x a 1n x n = b 1 a 21 x 1 + a 22 x a 2n x n = b 2.

3.2. Solving quadratic equations. Introduction. Prerequisites. Learning Outcomes. Learning Style

2x + y = 3. Since the second equation is precisely the same as the first equation, it is enough to find x and y satisfying the system

Matrices 2. Solving Square Systems of Linear Equations; Inverse Matrices

is identically equal to x 2 +3x +2

is identically equal to x 2 +3x +2

5 Systems of Equations

MATH10212 Linear Algebra. Systems of Linear Equations. Definition. An n-dimensional vector is a row or a column of n numbers (or letters): a 1.

Using row reduction to calculate the inverse and the determinant of a square matrix

1 Introduction to Matrices

Linear Programming. March 14, 2014

3.3. Solving Polynomial Equations. Introduction. Prerequisites. Learning Outcomes

1 Determinants and the Solvability of Linear Systems

Typical Linear Equation Set and Corresponding Matrices

Sequences. A sequence is a list of numbers, or a pattern, which obeys a rule.

Systems of Linear Equations

Linear Equations ! $ & " % & " 11,750 12,750 13,750% MATHEMATICS LEARNING SERVICE Centre for Learning and Professional Development

Circuits. The light bulbs in the circuits below are identical. Which configuration produces more light? (a) circuit I (b) circuit II (c) both the same

Solving Linear Systems, Continued and The Inverse of a Matrix

Solving Systems of Linear Equations

LS.6 Solution Matrices

Continued Fractions and the Euclidean Algorithm

Example: Determine the power supplied by each of the sources, independent and dependent, in this circuit:

Operation Count; Numerical Linear Algebra

Analysis of a single-loop circuit using the KVL method

Experiment NO.3 Series and parallel connection

Row Echelon Form and Reduced Row Echelon Form

What is Linear Programming?

SYSTEMS OF EQUATIONS AND MATRICES WITH THE TI-89. by Joseph Collison

7.4. The Inverse of a Matrix. Introduction. Prerequisites. Learning Style. Learning Outcomes

x = + x 2 + x

Linear Algebra Notes for Marsden and Tromba Vector Calculus

MATHEMATICS FOR ENGINEERS BASIC MATRIX THEORY TUTORIAL 2

Lecture 1: Systems of Linear Equations

1.4. Arithmetic of Algebraic Fractions. Introduction. Prerequisites. Learning Outcomes

The Characteristic Polynomial

MATHEMATICS FOR ENGINEERING BASIC ALGEBRA

Linear Programming Notes V Problem Transformations

Introduction to Matrices for Engineers

Factoring Quadratic Expressions

Circuit Analysis using the Node and Mesh Methods

Solving Systems of Linear Equations

The Method of Partial Fractions Math 121 Calculus II Spring 2015

Notes on Orthogonal and Symmetric Matrices MENU, Winter 2013

1.2 Solving a System of Linear Equations

10.2 Systems of Linear Equations: Matrices

CHAPTER 2. Eigenvalue Problems (EVP s) for ODE s

Series and Parallel Resistive Circuits

1 Lecture: Integration of rational functions by decomposition

Partial Fractions. p(x) q(x)

Preamble. Kirchoff Voltage Law (KVL) Series Resistors. In this section of my lectures we will be. resistor arrangements; series and

Excel supplement: Chapter 7 Matrix and vector algebra

Introduction to Matrix Algebra

Chapter 9. Systems of Linear Equations

Linear Algebra Notes

Solving Systems of Two Equations Algebraically

DERIVATIVES AS MATRICES; CHAIN RULE

160 CHAPTER 4. VECTOR SPACES

Lecture L3 - Vectors, Matrices and Coordinate Transformations

MATH APPLIED MATRIX THEORY

Integrating algebraic fractions

Basic Laws Circuit Theorems Methods of Network Analysis Non-Linear Devices and Simulation Models

1.5 SOLUTION SETS OF LINEAR SYSTEMS

CITY UNIVERSITY LONDON. BEng Degree in Computer Systems Engineering Part II BSc Degree in Computer Systems Engineering Part III PART 2 EXAMINATION

Second Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients. y + p(t) y + q(t) y = g(t), g(t) 0.

December 4, 2013 MATH 171 BASIC LINEAR ALGEBRA B. KITCHENS

Systems of Equations

Arithmetic and Algebra of Matrices

13 MATH FACTS a = The elements of a vector have a graphical interpretation, which is particularly easy to see in two or three dimensions.

1 Solving LPs: The Simplex Algorithm of George Dantzig

Name: Section Registered In:

CURVE FITTING LEAST SQUARES APPROXIMATION

Experiment #5, Series and Parallel Circuits, Kirchhoff s Laws

Solving Mass Balances using Matrix Algebra

Unified Lecture # 4 Vectors

EL-9650/9600c/9450/9400 Handbook Vol. 1

University of Lille I PC first year list of exercises n 7. Review

THE DIMENSION OF A VECTOR SPACE

Nodal and Loop Analysis

DC mesh current analysis

Systems of Linear Equations

Part 1 Expressions, Equations, and Inequalities: Simplifying and Solving

CHAPTER 28 ELECTRIC CIRCUITS

Solutions to Math 51 First Exam January 29, 2015

Solving Linear Equations - General Equations

Solve addition and subtraction word problems, and add and subtract within 10, e.g., by using objects or drawings to represent the problem.

LINEAR EQUATIONS IN TWO VARIABLES

The Gamma Match. 1 Equal Size Elements

5.4 Solving Percent Problems Using the Percent Equation

Transcription:

Solution by Inverse Matrix Method 8.2 Introduction The power of matrix algebra is seen in the representation of a system of simultaneous linear equations as a matrix equation. Matrix algebra allows us to write the solution of the system using the inverse matrix of the coefficients. In practice the method is suitable only for small systems. Its main use is the theoretical insight into such problems which it provides. Prerequisites Before starting this Section you should... Learning Outcomes On completion you should be able to... be familiar with the basic rules of matrix algebra be able to evaluate 2 2 and 3 3 determinants be able to find the inverse of 2 2 and 3 3 matrices use the inverse matrix of coefficients to solve a system of two linear simultaneous equations use the inverse matrix of coefficients to solve a system of three linear simultaneous equations recognise and identify cases where there is no solution or no unique solution 13

1. Solving a system of two equations using the inverse matrix If we have one linear equation ax b in which the unknown is x and a and b are constants and a 0 then x b a a 1 b. What happens if we have more than one equation and more than one unknown? In this Section we copy the algebraic solution x a 1 b used for a single equation to solve a system of linear equations. As we shall see, this will be a very natural way of solving the system if it is first written in matrix form. Consider the system 2x 1 + 3x 2 5 x 1 2x 2 1. In matrix form this becomes [ [ [ 2 3 x1 5 1 x 2 If A 1 exists then the solution is X A 1 B. which is of the form AX B. (compare the solution x a 1 b above) Given the matrix A about A 1? [ 2 3 find its determinant. What does this tell you A 2 ( 2) 1 3 7 since A 0 then A 1 exists. Now find A 1 A 1 1 [ 2 3 ( 7) 1 2 1 7 [ 2 3 14 Workbook 8: Matrix Solution of Equations

Solve the system AX B where A [ 2 3 and B is [ 5 1. X A 1 B 1 7 [ 2 3 [ 5 1 1 7 [ 7 7 [ 1 1. Hence x 1 1, x 2 1. Use the inverse matrix method to solve 2x 1 + 3x 2 3 5x 1 + 4x 2 11 AX B is [ [ 2 3 x1 5 4 x 2 [ 3 11 A 2 4 3 5 7 and A 1 1 7 Using X A 1 B: [ x1 X 1 x 2 7 So x 1 3, x 2 1 [ 4 3 5 2 [ [ 4 3 3 1 [ 4 3 3 11 1 5 2 11 7 5 3 + 2 11 7 [ [ 21 3 7 1 15

Engineering Example 2 Currents in two loops In the circuit shown find the currents (i 1, i 2 ) in the loops. 3v 6Ω 5Ω 3Ω i 1 4v i 2 Figure 1 Solution We note that the current across the 3 Ω resistor (travelling top to bottom in the diagram) is given by (i 1 i 2 ). With this proviso we can apply Kirchhoff s law: In the left-hand loop 3(i 1 i 2 ) + 5i 1 3 8i 1 3i 2 3 In the right-hand loop 3(i 2 i 1 ) + 6i 2 4 3i 1 + 9i 2 4 In matrix form: [ [ [ 8 3 i1 3 3 9 i 2 4 [ 8 3 The inverse of is 1 [ 9 3 so solving gives 3 9 63 3 8 [ i1 1 [ [ 9 3 3 1 [ 39 i 2 63 3 8 4 63 41 so i 1 39 63 i 2 41 63 16 Workbook 8: Matrix Solution of Equations

2. Non-unique solutions The key to obtaining a unique solution of the system AX B is to find A 1. What happens when A 1 does not exist? Consider the system 2x 1 + 3x 2 5 4x 1 + 6x 2 In matrix form this becomes [ [ [ 2 3 x1 5 4 6 x 2. (1) (2) Identify the matrix A and hence find A 1. [ 2 3 A and A 2 6 4 3 0. Hence A 4 6 1 does not exist. Looking at the original system we see that Equation (2) is simply Equation (1) with all coefficients doubled. In effect we have only one equation for the two unknowns x 1 and x 2. The equations are consistent and have infinitely many solutions. If we let x 2 assume a particular value, t say, then x 1 must take the value x 1 1 (5 3t) i.e. the 2 solution to the given equations is: x 2 t, x 1 1 (5 3t), where t is called a parameter. 2 For each value of t there are unique values for x 1 and x 2 which satisfy the original system of equations. For example, if t 1, then x 2 1, x 1 1, if t 3 then x 2 3, x 1 7 and so on. Now consider the system 2x 1 + 3x 2 5 4x 1 + 6x 2 9 Since the left-hand sides are the same as those in the previous system then A is the same and again A 1 does not exist. There is no solution to the Equations (3) and (4). However, if we double Equation (3) we obtain 4x 1 + 6x 2, which conflicts with Equation (4). There are thus no solutions to (3) and (4) and the equations are said to be inconsistent. (3) (4) 17

What can you conclude about the solutions of the following systems? x 1 2x 2 1 3x 1 6x 2 3 3x 1 + 2x 2 7 6x 1 4x 2 5 First write the systems in matrix form and find A : [ [ [ x1 1 3 6 x 2 3 [ [ [ 3 2 x1 7 6 4 5 x 2 A 6 + 6 0; A 12 + 12 0. Now compare the two equations in each system in turn: The second equation is 3 times the first equation. There are infinitely many solutions of the form x 2 t, x 1 1 + 2t where t is arbitrary. If we multiply the first equation by ( 2) we obtain 6x 1 4x 2 14 which is in conflict with the second equation. The equations are inconsistent and have no solution. 3. Solving three equations in three unknowns It is much more tedious to use the inverse matrix to solve a system of three equations although in principle, the method is the same as for two equations. Consider the system x 1 2x 2 + x 3 3 2x 1 + x 2 x 3 5 3x 1 x 2 + 2x 3 12 We met this system in Section 8.1 where we found that A. Hence A 1 exists. 18 Workbook 8: Matrix Solution of Equations

Find A 1 by the method of determinants. First form the matrix where each element of A is replaced by its minor: 1 1 1 2 2 1 1 2 2 1 1 1 2 1 3 2 1 1 3 2 1 1 2 1 2 1 3 1 3 1 2 1 1 7 5 3 1 5 1 3 5. Now use the 3 3 array of signs to obtain the matrix of cofactors: The array of signs is + + + + + so that we obtain Now transpose this matrix and divide by A to obtain A 1 : 1 7 5 3 1 5 1 3 5. Transposing gives 1 3 1 7 1 3 5 5 5. Finally, A 1 1 1 3 1 7 1 3 5 5 5. 19

Now use X A 1 B to solve the system of linear equations: X 1 1 3 1 7 1 3 5 5 5 3 5 12 1 30 20 3 1 2 Then x 1 3, x 2 1, x 3 2. Comparing this approach to the use of Cramer s rule for three equations (in subsection 2 of Section 8.1) we can say that the two methods are both rather tedious! Equations with no unique solution If A 0, A 1 does not exist and therefore it is easy to see that the system of equations has no unique solution. But it is not obvious whether this is because the equations are inconsistent and have no solution or whether they are consistent and have infinitely many solutions. Consider the systems x 1 x 2 + x 3 4 2x 1 + 3x 2 2x 3 3 3x 1 + 2x 2 x 3 7 x 1 x 2 + x 3 4 2x 1 + 3x 2 2x 3 3 x 1 11x 2 + 9x 3 13 In system add the first equation to the second. What does this tell you about the system? The sum is 3x 1 + 2x 2 x 3 7, which is identical to the third equation. Thus, essentially, there are only two equations x 1 x 2 + x 3 4 and 3x 1 + 2x 2 x 3 7. Now adding these two gives 4x 1 + x 2 11 or x 2 11 4x 1 and then x 3 4 x 1 + x 2 4 x 1 + 11 4x 1 15 5x 1 Hence if we give x 1 a value, t say, then x 2 11 4t and x 3 15 5t. Thus there is an infinite number of solutions (one for each value of t). 20 Workbook 8: Matrix Solution of Equations

In system take the combination 5 times the first equation minus 2 times the second equation. What does this tell you about the system? The combination is x 1 11x 2 + 9x 3 14, which conflicts with the third equation. There is thus no solution. In practice, systems containing three or more linear equations are best solved by the method which we shall introduce in Section 8.3. Exercises 1. Solve the following using the inverse matrix method: 2x 3y 1 4x + 4y 2 2x 5y 2 4x + y 1 2. Solve the following equations using matrix methods: (c) 6x y 0 2x 4y 1 2x 1 + x 2 x 3 0 x 1 + x 3 4 x 1 + x 2 + x 3 0 x 1 x 2 + x 3 1 x 1 + x 3 1 x 1 + x 2 x 3 0 s 1. x 1 2, y 0 A 1 does not exist. (c) x 1 22, y 3 11 2. x 1 8 3, x 2 4, x 3 4 3 x 1 1 2, x 2 1, x 3 3 2 21