# Differential Equations

## Presentation on theme: "Differential Equations"— Presentation transcript:

Differential Equations

Chapter 6 Systems of First Order Linear Equations
we build on elementary theory and solution techniques for first order linear systems Science and engineering applications that possess even a modest degree of complexity often lead to systems of differential equations of dimension n > 2.A large portion of Chapter 6 generalizes the eigenvalue method presented in Chapter 3 to constant coefficient linear systems of dimension n > 2.

Chapter 6 - Systems of First Order Linear Equations
6.1 Definitions and Examples 6.2 Basic Theory of First Order Linear Systems 6.3 Homogeneous Linear Systems with Constant Coefficients 6.4 Nondefective Matrices with Complex Eigenvalues 6.5 Fundamental Matrices and the Exponential of a Matrix 6.6 Nonhomogeneous Linear Systems 6.7 Defective Matrices

6.1 Definitions and Examples
Matrix-Valued Functions. The principal mathematical objects involved in the study of linear systems of differential equations are matrix-valued functions, or simply matrix functions. These objects are vectors or matrices whose elements are functions of t. We write The matrix P = P(t) is said to be continuous at t = t0 or on an interval I = (α, β) if each element of P is a continuous function at the given point or on the given interval. Similarly, P(t) is said to be differentiable if each of its elements is differentiable, and its derivative dP/dt is defined by Similarly, the integral of a matrix function is defined as

First Order Linear Systems: General Framework
The general form of a first order linear system of dimension n is x'1= p11(t)x1 + p12(t)x2 + ・・・ + p1n(t)xn + g1(t), x'2= p21(t)x1 + p22(t)x2 + ・・・ + p2n(t)xn + g2(t), ... x'n= pn1(t)x1 + pn2 (t)x2 + ・・・ + pnn(t)xn + gn(t) or using matrix notation, x' = P(t)x + g(t), P(t) is matrix of coefficients. g(t) the nonhomogeneous term of the system. If g(t) = 0 for all t ∈ I , then the system is said to be homogeneous; otherwise the system is said to be nonhomogeneous. The function g(t) is often referred to as the input, or forcing function.

First Order Linear Systems: General Framework (Ctd.)
The system is said to have a solution on the interval I if there exists a vector x = φ(t) with n components that is differentiable at all points in the interval I and satisfies Eq. at all points in this interval. In addition to the system of differential equations, if there is an initial condition of the form x(t0) = x0, where t0 is a specified value of t in I and x0 is a given constant vector with n components. The system and the initial condition together form an initial value problem. The components of x are again referred to as state variables and the vector x = φ(t) is referred to as the state of the system at time t.

Linear nth Order Equations.
An nth order linear differential equation in standard form is given by to obtain a unique solution, we need n initial conditions To transform Eq. into a system of n first order equations, we introduce the variables x1, x2, , xn defined by x1 = y, x2 = y', x3 = y'' , ..., xn = y(n−1). In Matrix

Applications Modeled by First Order Linear Systems
We discuss several examples of applications that illustrate how higher dimensional linear systems can arise. Coupled Mass-Spring Systems. Compartment Models. Linear Control Systems. The State Variable Approach to Circuit Analysis.

6.2 Basic Theory of First Order Linear Systems
THEOREM (Existence and Uniqueness for First Order Linear Systems). If P(t) and g(t) are continuous on an open interval I = (α, β), then there exists a unique solution x = φ(t) to the initial value problem x' = P(t)x + g(t), x(t0) = x0, where t0 is any point in I, and x0 is any constant vector with n components. Moreover the solution exists throughout the interval I.

THEOREM 6.2.2 (Principle of Superposition).
If x1, x2, , xk are solutions of the homogeneous linear system x' = P(t)x on the interval I = (α, β), then the linear combination c1x1 + c2x2 + ・・・ + ckxk is also a solution of the system on I.

DEFINITION 6.2.3 The n vector functions x1, x2, , xn are said to be linearly independent on an interval I if the only constants c1, c2, , cn such that c1x1(t) + ・・・ + cnxn(t) = 0 for all t ∈ I are c1=c2=. . . =cn = 0. If there exist constants c1, c2, , cn , not all zero, such that c1x1(t) + ・・・ + cnxn(t) = 0 is true for all t ∈ I , the vector functions are said to be linearly dependent on I.

Examples 1 2

DEFINITION 6.2.4 Let x1, , xn be n solutions of x' = P(t)x and let X(t) be the n×n matrix whose j th column is xj (t), j = 1, , n, The Wronskian W = W[x1, , xn] of the n solutions x1, , xn is defined by W[x1, , xn](t) = det X(t).

THEOREM 6.2.5 Let x1, , xn be solutions of x' = P(t)x on an interval I = (α, β) in which P(t) is continuous. (i) If x1, , xn are linearly independent on I, then W[x1, , xn](t) ≠ 0 at every point in I, (ii) If x1, , xn are linearly dependent on I, then W[x1, , xn](t) = 0 at every point in I.

THEOREM 6.2.6

Example

Theorem 6.2.7

Linear nth Order Equations. COROLLARY 6.2.8
If the functions p1(t), p2(t), , pn(t), and g(t) are continuous on the open intervalI = (α, β), then there exists exactly one solution y = φ(t) of the differential equation that also satisfies the initial conditions This solution exists throughout the interval I.

COROLLARY 6.2.9

A fundamental set of solutions and the general solution
The terminology for solutions of the nth order scalar equation is identical to that used for solutions of x' = P(t)x. A set of solutions y1, , yn such that W[ y1, , yn](t0) ≠ 0 for some t0∈ (α, β) is called a fundamental set of solutions for Eq. (28). The n-parameter family represented by the linear combination y = c1y1(t) + ・・ ・+cnyn(t), where c1, , cn are arbitrary constants, is called the general solution of Eq. (28). Corollary guarantees that each solution of Eq. (28) corresponds to some member of this n- parameter family of solutions.

Example Q: Show that y1(x)=x, y2(x)=x−1, and y3(x)=x2 constitute a fundamental set of solutions for x3 y'' + x2 y'' − 2xy' + 2y = 0 on I = (0,∞). A: 1. Substituting each of y1, y2, and y3 into Eq. show that they are solutions on the given interval. 2. Verify that the three functions are linearly independent on I, by computing the Wronskian 3. Apply Corollary

6.3 Homogeneous Linear Systems with Constant Coefficients
In this section, we extend the eigenvalue method to the system x' = Ax, where A is a real constant n × n matrix. As in Chapter 3, we assume solutions of the form x = eλtv, where the scalar λ and the constant n × 1 vector v are to be determined. Given a square matrix A, recall that the problem of (i) finding values of λ for which Eq. (A − λIn)v = 0 has nontrivial solution vectors v, and (ii) finding the corresponding nontrivial solutions, is known as the eigenvalue problem for A.

Three cases 1. A has a complete set of n linearly independent eigenvectors and all of the eigenvalues of A are real, 2. A has a complete set of n linearly independent eigenvectors and one or more complex conjugate pairs of eigenvalues, 3. A is defective, that is, there are one or more eigenvalues of A for which the geometric multiplicity is less than the algebraic multiplicity (see Appendix A.4).

The Matrix A Is Nondefective With Real Eigenvalues
THEOREM 6.3.1 Example

Real and Distinct Eigenvalues.
COROLLARY 6.3.2 EXAMPLE

Symmetric Matrices. Properties of the eigenvalues and eigenvectors of a real symmetric matrix A (see Appendix A.4): 1. All the eigenvalues λ1, , λn of A are real. 2. A has a complete set of n real and linearly independent eigenvectors v1, , vn. Furthermore eigenvectors corresponding to different eigenvalues are orthogonal to one another and all eigenvectors belonging to the same eigenvalue can be chosen to be orthogonal to one another.

Example Diffusion on a One-Dimensional Lattice with Reflecting Boundaries. the system describing diffusion on a lattice consisting of n = 3 points is expressed in matrix notation as Insert images

6.4 Nondefective Matrices with Complex Eigenvalues
In this section, we again consider a system of n linear homogeneous equations with constant coefficients, x' = Ax, where the coefficient matrix A is real-valued, nondefective, and has one or more complex eigenvalues. If λ = μ + iν and (λ, v) is an eigenpair of A and v = a + ib, where a and b are real constant n×1 vectors, then the vectors x1(t) = Re u(t) = eμt (a cos νt − b sin νt) x2(t) = Im u(t) = eμt (a sin νt + b cos νt) are real-valued solutions of Eq. and are linearly independent.

Nondefective Matrices with Complex Eigenvalues
If all of the eigenvectors of A, real and complex, are linearly independent, then a fundamental set of real solutions of x' = Ax consists of solutions of the form above associated with complex eigenvalues and solutions of the form eλjtvj associated with real eigenvalues. For example, suppose that λ1 = μ + iν, λ2 = μ − iν, and that λ3, , λn are all real and distinct. Let the corresponding eigenvectors be v1 = a + ib, v2 = a − ib, v3, , vn. Then the general solution of x' = Ax is x = c1x1(t) + c2x2(t) + c3eλ3tv3 + ・・・ + cneλnt vn, where x1(t) and x2(t) are given by above equations. We emphasize that this analysis applies only if the coefficient matrix A is real, for it is only then that complex eigenvalues and eigenvectors occur in conjugate pairs.

Example Answer: The general solution is

Plots of the components and A typical solution trajectory

Natural Frequencies and Principal Modes of Vibration.
Consider again the system of two masses and three springs shown in Figure. If we assume that there are no external forces, then F1(t) = 0, F2(t) = 0 and from Section 6.1 we get the homogeneous system

Natural Frequencies and Principal Modes of Vibration (Ctd.)
This system is said to have two degrees of freedom since there are two independent coordinates, x1 and x2, necessary to describe the motion of the system. If both masses will undergo harmonic motion at the same frequency, the frequency is called a natural frequency of the system, and the motion is called a principal mode of vibration. The principal mode of vibration corresponding to the lowest natural frequency is referred to as the first mode. The principal mode of vibration corresponding to the next higher frequency is called the second mode and so on.

Example Answer: The general solution for arbitrary constants c1, c2, c3, and c4 is

The first principal mode of vibration
The motions of m1 and m2 are in phase but have different amplitudes.

The second principal mode of vibration
The motions of m1 and m2 are 180 degrees out of phase and have different amplitudes.

Component plots Component plots of the solution corresponding to the initial condition x(0) = (0, 2, 0, 0)T