m
m
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<math> f(x) = \frac{1}{2} x^{T} Qx - x^{T}b+c, Q = Q^{T} > 0. </math>
 
<math> f(x) = \frac{1}{2} x^{T} Qx - x^{T}b+c, Q = Q^{T} > 0. </math>
 
<br><br>
 
<br><br>
'''(i)(10 pts) Find a closed form expression for <math>\alpha_k</math> in terms of <math>Q, H_k, g^{(k)}, and d^{(k)}; </math>'''
+
'''(i)(10 pts) Find a closed form expression for <math>\alpha_k</math> in terms of <math>Q, H_k, g^{(k)}</math>, and <math>d^{(k)}; </math>'''
 
<br>  
 
<br>  
 
'''(ii)(10 pts) Give a sufficient condition on <math>H_k</math> for <math>\alpha_k</math> to be positive.'''
 
'''(ii)(10 pts) Give a sufficient condition on <math>H_k</math> for <math>\alpha_k</math> to be positive.'''
Line 76: Line 76:
 
:'''Click [[QE2012_AC-3_ECE580-3|here]] to view [[QE2012_AC-3_ECE580-3|student answers and discussions]]'''  
 
:'''Click [[QE2012_AC-3_ECE580-3|here]] to view [[QE2012_AC-3_ECE580-3|student answers and discussions]]'''  
 
----
 
----
'''Problem 4. (20pts) Use any simplex method to solve the following linear program. '''  
+
'''Problem 4. (20pts) Consider the following model of a discrete-time system, '''  
 
+
<br>
            <span class="texhtml">''Maximize''</span>'''    <span class="texhtml">''x''<sub>1</sub> + 2''x''<sub>2</sub></span>'''
+
<math> x(k+1) = x(k) + 2u(k), x(0) = 3, 0 \le k \le 2</math>
        <span class="texhtml">''S'ubject to''</span>'''    <math>-2x_1+x_2 \le 2</math>'''
+
<br>
                        <math>x_1-x_2 \ge -3</math>
+
'''Use the Lagrange multiplier approach to calculate the optimal control sequence'''
                        <math>x_1 \le -3</math>
+
<br>
                        <math>x_1 \ge 0, x_2 \ge 0.</math>
+
{u(0), u(1), u(2)}
 +
<br>
 +
''' that transfers the initial state x(0) to x(3) = 9 while minimizing the performance index'''
 +
<br>
 +
<math> J = \frac{1}{2} \sum_{k=0}^2 u(k)^2 = \frac{1}{2}u^Tu. </math>
 +
<br>
 +
''' Hint: Use the system model to obtain a constraint of the form, <math>Au = b, A \in R^{1 \times 3}. </math>'''
  
 
:'''Click [[QE2012_AC-3_ECE580-4|here]] to view [[QE2012_AC-3_ECE580-4|student answers and discussions]]'''
 
:'''Click [[QE2012_AC-3_ECE580-4|here]] to view [[QE2012_AC-3_ECE580-4|student answers and discussions]]'''
 
----
 
----
  
<br> '''Problem 5.(20pts) Solve the following problem:'''  
+
<br> '''Problem 5.(20 pts) Problem 5. (20pts) Find minimizers and maximizers of the function, '''  
 
+
<br>
            <span class="texhtml">''Minimize''</span>'''    <math>-x_1^2 + 2x_2</math>'''
+
<math> f(x) = (a^Tx)(b^Tx), x \in R^3, </math>
        <span class="texhtml">''Subject to''</span>'''    <math>x_1^2+x_2^2 \le 1</math>'''
+
<br>
                        <math> x_1 \ge 0</math>
+
'''subject to'''
                        <math>x_2 \ge 0</math>
+
<br>
 
+
<math> x_1 + x_2 = 0
'''(i)(10pts) Find the points that satisfy the KKT condition.'''  
+
<br>
 
+
x_2 + x_3 = 0, </math>  
 
+
<br>
 
+
'''where'''
<br> '''(ii)(10pts)Apply the SONC and SOSC to determine the nature of the critical points from the previous part.'''
+
<br>
 +
<math>a = \begin{bmatrix}
 +
  0  \\
 +
  1 \\
 +
  0
 +
\end{bmatrix} and b = \begin{bmatrix}
 +
  1  \\
 +
  0 \\
 +
  1
 +
\end{bmatrix}</math>
  
 
:'''Click [[QE2012_AC-3_ECE580-5|here]] to view [[QE2012_AC-3_ECE580-5|student answers and discussions]]'''
 
:'''Click [[QE2012_AC-3_ECE580-5|here]] to view [[QE2012_AC-3_ECE580-5|student answers and discussions]]'''
 
----
 
----
 
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Revision as of 13:06, 23 January 2015


ECE Ph.D. Qualifying Exam

Automatic Control (AC)

Question 3: Optimization WORK IN PROGRESS

August 2013



Student answers and discussions for Part 1,2,3,4,5

1.(20 pts) In some of the optimization methods, when minimizing a given function f(x), we select an intial guess $ x^{(0)} $ and a real symmetric positive definite matrix $ H_{0} $. Then we computed $ d^{(k)} = -H_{k}g^{(k)} $, where $ g^{(k)} = \nabla f( x^{(k)} ) $, and $ x^{(k+1)} = x^{(k)} + \alpha_{k}d^{(k)} $, where
$ \alpha_{k} = arg\min_{\alpha \ge 0}f(x^{(k)} + \alpha d^{(k)}) . $
Suppose that the function we wish to minimize is a standard quadratic of the form,
$ f(x) = \frac{1}{2} x^{T} Qx - x^{T}b+c, Q = Q^{T} > 0. $

(i)(10 pts) Find a closed form expression for $ \alpha_k $ in terms of $ Q, H_k, g^{(k)} $, and $ d^{(k)}; $
(ii)(10 pts) Give a sufficient condition on $ H_k $ for $ \alpha_k $ to be positive.

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Problem 2. (20 pts) [(i) (10 pts)] Consider the one-point crossover of a chromosome in the schema
H = * 1 * 0 1 0 *
where the probability that a chromosome is chosen for crossover is $ p_c = 0.5. $ Find an upper bound on the probability that a chromosome from H will be destroyed by the one-point crossover.

[(ii) (10 pts)] Consider a chromosome in the schema
H = * 1 * 0 * * *
Find the probability that the mutation operation destroys the schema, where the probability of random change of each symbol of the chromosome is $ p_m = 0.1 $ independently.

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Problem 3. (20 pts) [(i) (10 pts)] Convert the following optimization problem into a linear programming problem and solve it;
maximize $ -|x_1| -|x_2| -|x_3| $
subject to
$ \begin{bmatrix} 1 & 1 &-1 \\ 0 & -1 & 0 \end{bmatrix} \begin{bmatrix} x_1 \\ x_2 \\ x_3 \end{bmatrix} = \begin{bmatrix} 2 \\ 1 \end{bmatrix} . $

[(ii) (10 pts)] Construct the dual program of the linear program above and solve it.

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Problem 4. (20pts) Consider the following model of a discrete-time system,
$ x(k+1) = x(k) + 2u(k), x(0) = 3, 0 \le k \le 2 $
Use the Lagrange multiplier approach to calculate the optimal control sequence
{u(0), u(1), u(2)}
that transfers the initial state x(0) to x(3) = 9 while minimizing the performance index
$ J = \frac{1}{2} \sum_{k=0}^2 u(k)^2 = \frac{1}{2}u^Tu. $
Hint: Use the system model to obtain a constraint of the form, $ Au = b, A \in R^{1 \times 3}. $

Click here to view student answers and discussions


Problem 5.(20 pts) Problem 5. (20pts) Find minimizers and maximizers of the function,
$ f(x) = (a^Tx)(b^Tx), x \in R^3, $
subject to
$ x_1 + x_2 = 0 <br> x_2 + x_3 = 0, $
where
$ a = \begin{bmatrix} 0 \\ 1 \\ 0 \end{bmatrix} and b = \begin{bmatrix} 1 \\ 0 \\ 1 \end{bmatrix} $

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