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In Exercises 3-6, solve the initial value problem \(x'\left( t \right) = Ax\left( t \right)\) for \(t \ge 0\), with \(x\left( 0 \right) = \left( {3,2} \right)\). Classify the nature of the origin as an attractor, repeller, or saddle point of the dynamical system described by \(x' = Ax\). Find the directions of greatest attraction and/or repulsion. When the origin is a saddle point, sketch typical trajectories.

4. \(A = \left( {\begin{aligned}{ {20}{c}}{ - 2}&{ - 5}\\1&4\end{aligned}} \right)\)

Short Answer

Expert verified

The required solution is:

\({\rm{x}}\left( t \right) = \frac{{13}}{4}\left( {\begin{aligned}{ {20}{c}}{ - 1}\\1\end{aligned}} \right){e^{3t}} - \frac{5}{4}\left( {\begin{aligned}{ {20}{c}}{ - 5}\\1\end{aligned}} \right){e^{ - t}}\)

The origin is a saddle point.

The direction of greatest repulsion is through the origin, and the eigenvector is\({v_1} = \left( {\begin{aligned}{ {20}{c}}{ - 1}\\1\end{aligned}} \right)\).

The direction of greatest attraction is through the origin and eigenvector is \({v_2} = \left( {\begin{aligned}{ {20}{c}}{ - 5}\\1\end{aligned}} \right)\).

Step by step solution

01

System of Differential Equations

The general solutionfor any system of differential equations withthe eigenvalues\({\lambda _1}\)and\({\lambda _2}\)with the respective eigenvectors\({v_1}\)and\({v_2}\)is given by:

\(x(t) = {c_1}{v_1}{e^{{\lambda _1}t}} + {c_2}{v_2}{e^{{\lambda _2}t}}\)

Here \({c_1}\) and \({c_2}\) are the constants from the initial condition.

02

Find the eigenvalues.

According to the question, we have:

\(A = \left( {\begin{aligned}{ {20}{c}}{ - 2}&{ - 5}\\1&4\end{aligned}} \right)\)

For eigenvalues:

\(\begin{aligned}{c}\det (A - \lambda I) = 0\\( - 2 - \lambda )(4 - \lambda ) + 5 = 0\\ - 3 - 2\lambda + {\lambda ^2} = 0\\{\lambda _1} = 3,{\lambda _2} = - 1\end{aligned}\)

The obtained eigenvalues are 3 and\( - 1\).

Hence, the origin is a saddle point.

03

Find eigenvectors for both eigenvalues

Now, for\({\lambda _1} = 3\)we have:

\(A = \left( {\begin{aligned}{ {20}{c}}{ - 5}&{ - 5}&0\\1&1&0\end{aligned}} \right)\~\left( {\begin{aligned}{ {20}{c}}1&1&0\\0&0&0\end{aligned}} \right)\)

So,\({x_1} = - {x_2}\)with\({x_2}\)free.

Taking\({x_2} = 1\), we get, eigenvector:

\({v_1} = \left( {\begin{aligned}{ {20}{l}}{ - 1}\\1\end{aligned}} \right)\)

Similarly,for\({\lambda _2} = - 1\)we have:

\(A = \left( {\begin{aligned}{ {20}{c}}{ - 1}&{ - 5}&0\\1&5&0\end{aligned}} \right)\~\left( {\begin{aligned}{ {20}{l}}1&5&0\\0&0&0\end{aligned}} \right)\)

So\({x_1} = - 5{x_2}\)with\({x_2}\)free.

Taking\({x_2} = 1\), we get:

\({v_2} = \left( {\begin{aligned}{ {20}{l}}{ - 5}\\1\end{aligned}} \right)\)

Using both eigenvectors, we have:

\(\left( {\begin{aligned}{ {20}{l}}{{v_1}}&{{v_2}}&{x(0)}\end{aligned}} \right) = \left( {\begin{aligned}{ {20}{c}}{ - 1}&{ - 5}&3\\1&1&2\end{aligned}} \right)\~\left( {\begin{aligned}{ {20}{c}}1&0&{\frac{{13}}{4}}\\0&1&{ - \frac{5}{4}}\end{aligned}} \right)\)

Thus,\({c_1} = \frac{{13}}{4}\)and\({c_2} = - \frac{5}{4}\).

Now, the general solution will be:

\(x(t) = \frac{{13}}{4}\left( {\begin{aligned}{ {20}{c}}{ - 1}\\1\end{aligned}} \right){e^{3t}} - \frac{5}{4}\left( {\begin{aligned}{ {20}{c}}{ - 5}\\1\end{aligned}} \right){e^{ - t}}\)

Hence, this is the required solution.

04

Find the directions of greatest attraction and/or repulsion

Since one eigenvalue is less than 1 and the other is greater, so the origin is a saddle point of the dynamical system described by\(x\prime = Ax\).

The direction of greatest repulsion is through the origin and eigenvector:\({v_1} = \left( {\begin{aligned}{ {20}{c}}{ - 1}\\1\end{aligned}} \right)\).

The direction of greatest attraction is through the origin and eigenvector: \({v_2} = \left( {\begin{aligned}{ {20}{c}}{ - 5}\\1\end{aligned}} \righ

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Most popular questions from this chapter

Consider the growth of a lilac bush. The state of this lilac bush for several years (at yearโ€™s end) is shown in the accompanying sketch. Let n(t) be the number of new branches (grown in the year t) and a(t) the number of old branches. In the sketch, the new branches are represented by shorter lines. Each old branch will grow two new branches in the following year. We assume that no branches ever die.

(a) Find the matrix A such that [nt+1at+1]=A[ntat]

(b) Verify that [11]and [2-1] are eigenvectors of A. Find the associated eigenvalues.

(c) Find closed formulas for n(t) and a(t).

Consider an invertible n ร— n matrix A such that the zero state is a stable equilibrium of the dynamical system xโ†’(t+1)=ATxโ†’(t)What can you say about the stability of the systems.

xโ†’(t+1)=ATxโ†’(t)

Question: Find the characteristic polynomial and the eigenvalues of the matrices in Exercises 1-8.

7. \(\left[ {\begin{array}{*{20}{c}}5&3\\- 4&4\end{array}} \right]\)

Question: Is \(\left( {\begin{array}{*{20}{c}}{ - 1 + \sqrt 2 }\\1\end{array}} \right)\) an eigenvalue of \(\left( {\begin{array}{*{20}{c}}2&1\\1&4\end{array}} \right)\)? If so, find the eigenvalue.

Question: Diagonalize the matrices in Exercises \({\bf{7--20}}\), if possible. The eigenvalues for Exercises \({\bf{11--16}}\) are as follows:\(\left( {{\bf{11}}} \right)\lambda {\bf{ = 1,2,3}}\); \(\left( {{\bf{12}}} \right)\lambda {\bf{ = 2,8}}\); \(\left( {{\bf{13}}} \right)\lambda {\bf{ = 5,1}}\); \(\left( {{\bf{14}}} \right)\lambda {\bf{ = 5,4}}\); \(\left( {{\bf{15}}} \right)\lambda {\bf{ = 3,1}}\); \(\left( {{\bf{16}}} \right)\lambda {\bf{ = 2,1}}\). For exercise \({\bf{18}}\), one eigenvalue is \(\lambda {\bf{ = 5}}\) and one eigenvector is \(\left( {{\bf{ - 2,}}\;{\bf{1,}}\;{\bf{2}}} \right)\).

11. \(\left( {\begin{array}{*{20}{c}}{ - 1}&4&{ - 2}\\{ - 3}&4&0\\{ - 3}&1&3\end{array}} \right)\)

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