Difference between revisions of "CDS 140a Winter 2014 Homework 2"
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{{CDS homework  {{CDS homework  
 instructor = R. Murray   instructor = R. Murray  
 course = ACM   course = ACM 101b/AM 125b/CDS 140a  
 semester = Winter   semester = Winter 2014  
 title = Problem Set #2   title = Problem Set #2  
 issued =   issued = 14 Jan 2014 (Tue)  
 due =   due = 22 Jan 2014 (Wed) @ noon <br>Turn in to box outside Steele House  
}}  }}  
<! 2014 feedback from TA office hours  
TA1: There were a lot of questions on problem 3. Also, quite a few students either had serious issues with linear algebra or even explicitly said that their linear algebra was poor, so it might be a good idea to do that linear algebra recitation.  
TA2: I also had a lot of questions on problem 3, and also a lot of questions on problem 1a. Two or three persons had some questions on how to compute generalized eigenvectors, and why there are different methods. I gave a brief explanation of how to compute generalized eigenvectors according to the method of Perko (around page 42, depending on the copy of Perko), as one of the students had questions about that, but didn't get into all of the details. That method I believe is a good method and better than other methods I've seen. An example of computing generalized eigenvectors for a 3x3 matrix seemed to be helpful to show some of the students. A lot of people (some in office hours) are not familiar with how to compute e^{Jt} for a Jordan form with off diagonal elements (ones).  
>  
'''Note:''' In the upper left hand corner of the ''second'' page of your homework set, please put the number of hours that you spent on  '''Note:''' In the upper left hand corner of the ''second'' page of your homework set, please put the number of hours that you spent on  
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</li>  </li>  
<li> '''Perko, Section 1.9, problem 5, parts (c),  <li> '''Perko, Section 1.9, problem 5, parts (c), (d2)''': Let <amsmath>A</amsmath> be an <amsmath>n \times n</amsmath> nonsingular matrix and let <amsmath>x(t)</amsmath> be the solution of the initial value problem (1) with <amsmath>x(0) = x_0</amsmath>. Show that<br>  
(c) If <amsmath>x_0 \in E^c</amsmath>, <amsmath>x_0 \neq 0</amsmath> and <amsmath>A</amsmath> is semisimple, then there are postive constants <amsmath>m</amsmath> and <amsmath>M</amsmath> such that for all <amsmath>t \in R</amsmath>, <amsmath>m \leq x(t) \leq M</amsmath>;  (c) If <amsmath>x_0 \in E^c</amsmath>, <amsmath>x_0 \neq 0</amsmath> and <amsmath>A</amsmath> is semisimple, then there are postive constants <amsmath>m</amsmath> and <amsmath>M</amsmath> such that for all <amsmath>t \in R</amsmath>, <amsmath>m \leq x(t) \leq M</amsmath>;  
:* Note: in the book, Perko defines <amsmath>\sim</amsmath> to mean "set subtraction". So <amsmath>E \sim \{0\}</amsmath> in the book is the set <amsmath>E</amsmath> minus the point 0.  :* Note: in the book, Perko defines <amsmath>\sim</amsmath> to mean "set subtraction". So <amsmath>E \sim \{0\}</amsmath> in the book is the set <amsmath>E</amsmath> minus the point 0.  
(d2) If <amsmath>E^s \neq \{0\}</amsmath>, <amsmath>E^u \neq \{0\}</amsmath>, and <amsmath>x_0</amsmath> has nonzero components in both <amsmath>E^s</amsmath> and <amsmath>E^u</amsmath>, then <amsmath>\lim_{t \to \pm \infty} x(t) = \infty</amsmath>;  (d2) If <amsmath>E^s \neq \{0\}</amsmath>, <amsmath>E^u \neq \{0\}</amsmath>, and <amsmath>x_0</amsmath> has nonzero components in both <amsmath>E^s</amsmath> and <amsmath>E^u</amsmath>, then <amsmath>\lim_{t \to \pm \infty} x(t) = \infty</amsmath>;  
</li>  </li>  
<! Replaced in 2014 with problem below  
<li> '''Perko, Section 1.10, problem 2''': Use Theorem 1 in Section 1.10 to solve the nonhomogeneous linear system  <li> '''Perko, Section 1.10, problem 2''': Use Theorem 1 in Section 1.10 to solve the nonhomogeneous linear system  
<center><amsmath>  <center><amsmath>  
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x(0) = \begin{bmatrix} 1 \\ 0 \end{bmatrix}.  x(0) = \begin{bmatrix} 1 \\ 0 \end{bmatrix}.  
</amsmath></center>  </amsmath></center>  
</li>  
>  
<li>  
Consider the system  
<center><amsmath>  
\frac{dx}{dt} = \begin{bmatrix} 0 & 1 \\ 1 & 0 \end{bmatrix} x + \begin{bmatrix} 0 \\ 1 \end{bmatrix}u, \qquad  
y = \begin{bmatrix} 1 & 0 \end{bmatrix} x.  
</amsmath></center>  
(a) Show that the unforced system (<amsmath>u = 0</amsmath>) is stable but not asymptotically stable.  
(b) Given <amsmath>x(0) = x_0</amsmath> and <amsmath>u(t) = \cos(\omega*t)</amsmath>, solve for the output <amsmath>y(t)</amsmath>. Show that when <amsmath>\omega=1</amsmath> the output is unbounded.  
</li>  </li>  
</ol>  </ol> 
Latest revision as of 00:02, 10 February 2014
R. Murray  Issued: 14 Jan 2014 (Tue) 
ACM 101b/AM 125b/CDS 140a, Winter 2014  Due: 22 Jan 2014 (Wed) @ noon Turn in to box outside Steele House 
Note: In the upper left hand corner of the second page of your homework set, please put the number of hours that you spent on
this homework set (including reading).
 Perko, Section 1.8, problem 10
Suppose that the elementary blocks <amsmath>B</amsmath> in the Jordan form of the matrix <amsmath>A</amsmath>, have no ones or <amsmath>I_2</amsmath> blocks off the diagonal, so that they are of the form
<amsmath> B = \begin{bmatrix}
\lambda & 0 & 0 & \dots & 0 \\ 0 & \lambda & 0 & \dots & 0 \\ \dots & & & & & \\ 0 & \dots & & \lambda & 0 \\ 0 & \dots & & 0 & \lambda
\end{bmatrix} \qquad\text{or}\qquad B = \begin{bmatrix}
D & 0 & 0 & \dots & 0 \\ 0 & D & 0 & \dots & 0 \\ \dots & & & & & \\ 0 & \dots & & D & 0 \\ 0 & \dots & & 0 & D
\end{bmatrix}, \quad D = \begin{bmatrix} a & b \\ b & a \end{bmatrix}.
</amsmath>(a) Show that if all of the eigenvalues of <amsmath>A</amsmath> have nonpositive real parts, then for each <amsmath>x_0 \in {\mathbb R}^n</amsmath> there is a positive constant <amsmath>M</amsmath> such that <amsmath>x(t) \leq M</amsmath> for all <amsmath>t \geq 0</amsmath> where <amsmath>x(t)</amsmath> is the solution of the initial value problem.
(b) Show via a simple counterexample that this is not true if the Jordan blocks have nonzero off diagonal entries (with the same constraint on the eigenvalues).
 Perko, Section 1.9, problem 3 (modified): Consider the linear system
<amsmath> \dot x = \begin{bmatrix} a & 0 & 0 & 0\\ a & 0 & b & 0 \\ a & 0 & b & 0 \\ a & a & 0 & b \end{bmatrix} x,
</amsmath>where <amsmath>a,\,b > 0</amsmath>.
(a) Compute the solutions to the differential equation. You should provide the matrices used to transform the system to Jordan form along with the appropriate matrix exponential of the relevant Jordan form matrix (you don't need to multiply everything out to get the solution in the original basis).
 Note: you should show the various (regular and generalized) eigenvectors associated with each eigenvalue. OK to check your answer with MATLAB, but be sure to show that you know how to solve it by hand.
(b) Find the stable, unstable and center subspaces for this system (in the original coordinates).
 Perko, Section 1.9, problem 5, parts (c), (d2): Let <amsmath>A</amsmath> be an <amsmath>n \times n</amsmath> nonsingular matrix and let <amsmath>x(t)</amsmath> be the solution of the initial value problem (1) with <amsmath>x(0) = x_0</amsmath>. Show that
(c) If <amsmath>x_0 \in E^c</amsmath>, <amsmath>x_0 \neq 0</amsmath> and <amsmath>A</amsmath> is semisimple, then there are postive constants <amsmath>m</amsmath> and <amsmath>M</amsmath> such that for all <amsmath>t \in R</amsmath>, <amsmath>m \leq x(t) \leq M</amsmath>; Note: in the book, Perko defines <amsmath>\sim</amsmath> to mean "set subtraction". So <amsmath>E \sim \{0\}</amsmath> in the book is the set <amsmath>E</amsmath> minus the point 0.

Consider the system
<amsmath> \frac{dx}{dt} = \begin{bmatrix} 0 & 1 \\ 1 & 0 \end{bmatrix} x + \begin{bmatrix} 0 \\ 1 \end{bmatrix}u, \qquad y = \begin{bmatrix} 1 & 0 \end{bmatrix} x.
</amsmath>(a) Show that the unforced system (<amsmath>u = 0</amsmath>) is stable but not asymptotically stable.
(b) Given <amsmath>x(0) = x_0</amsmath> and <amsmath>u(t) = \cos(\omega*t)</amsmath>, solve for the output <amsmath>y(t)</amsmath>. Show that when <amsmath>\omega=1</amsmath> the output is unbounded.
Notes:
 The problems are transcribed above in case you don't have access to Perko. However, in the case of discrepancy, you should use Perko as the definitive source of the problem statement.
 There are a number of problems that can be solved using MATLAB. If you just give the answer with no explanation (or say "via MATLAB"), the TAs will take off points. Instead, you should show how the solutions can be worked out by hand, along the lines of what is done in the textbook. It is fine to check everything with MATLAB.