Coupled Oscillator: Double Pendulum: Difference between revisions
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By '''Jimmy Apablaza''' |
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By '''Jimmy Apablaza''' |
By '''Jimmy Apablaza''' |
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'''Assumptions:''' |
'''Assumptions:''' |
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* the system oscillates vertically under the influence of gravity. |
* the system oscillates vertically under the influence of gravity. |
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* the mass of both rod are |
* the mass of both rod are negligible |
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* no |
* no damping forces act on the system |
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* positive direction to the right. |
* positive direction to the right. |
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== Solution == |
== Solution == |
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=== Laplace Transform === |
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Since our concern is about the motion functions, we will assign the masses <math>m_1</math> and <math>m_2</math>, the rod lenghts <math>l_1</math> and <math>l_1</math>, and gravitational force <math>g</math> constants to different variables as follows, |
Since our concern is about the motion functions, we will assign the masses <math>m_1</math> and <math>m_2</math>, the rod lenghts <math>l_1</math> and <math>l_1</math>, and gravitational force <math>g</math> constants to different variables as follows, |
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Hence, |
Hence, |
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: <math>A\theta_1^{ |
: <math>A\theta_1^{''} + B\theta_2^{''} + C\theta_1 = 0</math> |
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: <math>D\theta_2^{ |
: <math>D\theta_2^{''} + B\theta_1^{''} + E\theta_2 = 0</math> |
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Solving for <math>\theta_1^{''}</math> and <math>\theta_2^{''}</math> we obtain, |
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Solving the Laplace Transform system yeilds, |
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: <math> |
: <math>\theta_1^{''} = - \left ( \dfrac{B}{A} \right ) \theta_2^{''} - \left ( \dfrac{C}{A} \right ) \theta_1</math> |
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: <math>\theta_2^{''} = - \left ( \dfrac{B}{D} \right ) \theta_1^{''} - \left ( \dfrac{E}{D} \right ) \theta_2</math> |
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Therefore, |
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: <math>D(s^2\boldsymbol{\Theta}_2-s\theta_2-\theta_2^{\prime}) + B(s^2\boldsymbol{\Theta}_1-s\theta_1-\theta_1^{\prime}) + E\boldsymbol{\Theta}_2 = 0</math> |
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: <math>\theta_1^{''} = - \left ( \dfrac{CD}{AD+B^2} \right ) \theta_1 - \left ( \dfrac{BE}{AD+B^2} \right ) \theta_2 </math> |
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At time <math>t=0</math> we assume that <math>\theta_1(t)^{\prime}=\theta_2(t)^{\prime}=0</math>. Thus, solvin for <math>\boldsymbol{\Theta}_1</math> and <math>\boldsymbol{\Theta}_2</math> we obtain, |
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: <math>\theta_2^{''} = \left ( \dfrac{BC}{AD+B^2} \right ) \theta_1 - \left ( \dfrac{AE}{AD+B^2} \right ) \theta_2</math> |
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=== State Space === |
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: <math>\boldsymbol{\Theta}_1=\dfrac{sA\theta_1+sB\theta_2-s^2B\boldsymbol{\Theta}_2}{(s^2A+C)}</math> |
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: <math>\boldsymbol{\Theta}_2=\dfrac{sB\theta_1+sD\theta_2-s^2B\boldsymbol{\Theta}_1}{(s^2D+E)}</math> |
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: <math> |
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\begin{bmatrix} |
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\theta_1^{'} \\ \theta_1^{''} \\ \theta_2^{'} \\ \theta_2^{''} |
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\end{bmatrix} |
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= |
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\widehat{A} \, \underline{x}(t) + \widehat{B} \, \underline{u}(t) |
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=== State Space === |
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= |
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\begin{bmatrix} |
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0 & 1 & 0 & 0 \\ |
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& & & \\ |
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\dfrac{-CD}{AD-B^2} & 0 & \dfrac{BE}{AD-B^2} & 0 \\ |
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& & & \\ |
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0 & 0 & 0 & 1 \\ |
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& & & \\ |
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\dfrac{BC}{AD-B^2} & 0 & \dfrac{-AE}{AD-B^2} & 0 \\ |
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\end{bmatrix} |
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\begin{Bmatrix} |
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\theta_1 \\ \theta_1^{'} \\ \theta_2 \\ \theta_2^{'} |
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\end{Bmatrix} |
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+ |
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\widehat{0} |
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</math> |
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Let's plug some numbers. It's known that <math>g=32</math>. In addition, we assume that <math>m_1=3</math>, <math>m_2=1</math>, and <math>l_1=l_2=16</math>, so the constants defined previously become, |
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: <math>A=1024 \quad B=256 \quad C=2048 \quad D=256 \quad E=512</math> |
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Hence, the state space matrix is, |
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: <math> |
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\begin{bmatrix} |
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\theta_1^{'} \\ \theta_1^{''} \\ \theta_2^{'} \\ \theta_2^{''} |
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\end{bmatrix} |
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= |
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\begin{bmatrix} |
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0 & 1 & 0 & 0 \\ |
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-\dfrac{8}{3} & 0 & \dfrac{2}{3} & 0 \\ |
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0 & 0 & 0 & 1 \\ |
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\dfrac{8}{3} & 0 & -\dfrac{8}{3} & 0 \\ |
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\end{bmatrix} |
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\begin{Bmatrix} |
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\theta_1 \\ \theta_1^{'} \\ \theta_2 \\ \theta_2^{'} |
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\end{Bmatrix} |
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</math> |
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=== Eigenvalues & Eigenvectors === |
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The eigenvalues and eigenvectors are easily obtained with the help of a TI-89 calculator. First, we consider the <math>\widehat{A}</math>'s identity matrix, |
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: <math> |
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[\lambda I-A] |
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= |
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\begin{bmatrix} |
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\lambda & 1 & 0 & 0 \\ |
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-\dfrac{8}{3} & \lambda & \dfrac{2}{3} & 0 \\ |
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0 & 0 & \lambda & 1 \\ |
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\dfrac{8}{3} & 0 & -\dfrac{8}{3} & \lambda \\ |
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\end{bmatrix} |
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</math> |
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Once we define the <math>\widehat{A}</math> matrix, the eigenvalues are determined by using the '''''eigVi()''''' function, |
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: <math>\lambda_1= 2 \mathbf{i}</math> |
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: <math>\lambda_2= -2 \mathbf{i}</math> |
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: <math>\lambda_3= 1.1547 \mathbf{i}</math> |
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: <math>\lambda_4= -1.1547 \mathbf{i}</math> |
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On the other hand, we use the '''''eigVc()''''' function to find the eigenvectors, |
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: <math> |
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k_1 |
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= |
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\begin{bmatrix} |
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-0.2 \mathbf{i} \\ |
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0.4 \\ |
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0.4 \mathbf{i} \\ |
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-0.8 \\ |
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\end{bmatrix} |
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\quad |
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k_2 |
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= |
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\begin{bmatrix} |
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0.2 \mathbf{i} \\ |
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0.4 \\ |
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-0.4 \mathbf{i} \\ |
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-0.8 \\ |
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\end{bmatrix} |
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\quad |
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k_3 |
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= |
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\begin{bmatrix} |
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-0.29277 \mathbf{i} \\ |
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0.33806 \\ |
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0.58554 \mathbf{i} \\ |
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-0.67621 \\ |
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\end{bmatrix} |
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\quad |
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k_4 |
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= |
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\begin{bmatrix} |
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0.29277 \mathbf{i} \\ |
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0.33806 \\ |
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0.58554 \mathbf{i} \\ |
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0.67621 \\ |
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\end{bmatrix} |
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</math> |
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=== Standard Equation === |
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Now, we plug the eigenvalues and eigenvectors to produce the standar equation, |
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: <math>\underline{x} = c_1 \underline{k_1} e^{\lambda_1 t} + c_2 \underline{k}_2 e^{\lambda_2 t} + c_3 \underline{k_3} e^{\lambda_3 t} + c_4 \underline{k_4} e^{\lambda_4 t}</math> |
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: <math> |
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\underline{x} |
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= |
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c_1 |
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\begin{bmatrix} |
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-0.2 \mathbf{i} \\ |
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0.4 \\ |
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0.4 \mathbf{i} \\ |
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-0.8 \\ |
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\end{bmatrix} |
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e^{2 \mathbf{i}} |
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+ |
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c_2 |
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\begin{bmatrix} |
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0.2 \mathbf{i} \\ |
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0.4 \\ |
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-0.4 \mathbf{i} \\ |
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-0.8 \\ |
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\end{bmatrix} |
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e^{-2 \mathbf{i}} |
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+ |
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c_3 |
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\begin{bmatrix} |
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-0.29277 \mathbf{i} \\ |
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0.33806 \\ |
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0.58554 \mathbf{i} \\ |
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-0.67621 \\ |
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\end{bmatrix} |
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e^{1.1547 \mathbf{i}} |
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+ |
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c_4 |
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\begin{bmatrix} |
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0.29277 \mathbf{i} \\ |
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0.33806 \\ |
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0.58554 \mathbf{i} \\ |
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0.67621 \\ |
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\end{bmatrix} |
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e^{-1.1547 \mathbf{i}} |
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</math> |
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=== Matrix Exponential === |
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The matrix exponential is, |
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: <math>\dot{\bar{z}}=\hat{A}\bar{z}=TAT^{-1}\bar{z}</math> |
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where |
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: <math> |
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A |
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= |
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\begin{bmatrix} |
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0 & 1 & 0 & 0 \\ |
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-\dfrac{8}{3} & 0 & \dfrac{2}{3} & 0 \\ |
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0 & 0 & 0 & 1 \\ |
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\dfrac{8}{3} & 0 & -\dfrac{8}{3} & 0 \\ |
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\end{bmatrix} |
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</math>, |
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and |
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: <math> |
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T^{-1} |
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= |
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[k_1|k_2|k_3|k_4] |
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= |
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\begin{bmatrix} |
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-0.2 \mathbf{i} & 0.2 \mathbf{i} & -0.29277 \mathbf{i} & 0.29277 \mathbf{i} \\ |
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0.4 & 0.4 & 0.33806 & 0.33806 \\ |
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0.4 \mathbf{i} & -0.4 \mathbf{i} & 0.58554 \mathbf{i} & 0.58554 \mathbf{i} \\ |
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-0.8 & -0.8 & -0.67621 & 0.67621 \\ |
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\end{bmatrix} |
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</math>, |
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so |
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: <math> |
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T |
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= |
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(T^{-1})^{-1} |
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= |
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[k_1|k_2|k_3|k_4]^{-1} |
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= |
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\begin{bmatrix} |
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1.25 \mathbf{i} & 0.625 & -0.625 \mathbf{i} & -0.3125 \\ |
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-1.25 \mathbf{i} & 0.625 & 0.625 \mathbf{i} & -0.3125 \\ |
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0.853913 \mathbf{i} & 0.73951 & 0.426956 \mathbf{i} & 0.369755 \\ |
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-0.853913 \mathbf{i} & 0.73951 & -0.426956 \mathbf{i} & 0.369755 \\ |
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\end{bmatrix} |
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</math> |
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Again, we can resort to the TI-89 calculator. As it is mentioned above, the matrix exponential is obtained by typing '''''eigVc(a)^-1*a*eigVc(a)''''', where '''''a''''' is the <math>\widehat{A}</math> matrix. Thus, |
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: <math> |
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\dot{\bar{z}} |
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= |
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\hat{A}\bar{z} |
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= |
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TAT^{-1}\bar{z} |
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= |
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\begin{bmatrix} |
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2 \mathbf{i} & 0 & 0 & 0 \\ |
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0 & -2 \mathbf{i} & 0 & 0 \\ |
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0 & 0 & 1.1547 \mathbf{i} & 0 \\ |
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0 & 0 & 0 & -1.1547 \mathbf{i} \\ |
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\end{bmatrix} |
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\bar{z} |
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</math> |
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So, the exponential matrix becomes, |
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:<math> |
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\dot{\underline{x}}=\widehat{A}\underline{x}=T^{-1}e^{\hat{A}t}T\underline{x}=e^{At}\underline{x} |
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</math> |
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where |
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:<math> |
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e^{\hat{A}t} |
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= |
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\begin{bmatrix} |
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e^{2 \mathbf{i} t} & 0 & 0 & 0 \\ |
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0 & e^{-2 \mathbf{i} t} & 0 & 0 \\ |
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0 & 0 & e^{1.1547 \mathbf{i} t} & 0 \\ |
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0 & 0 & 0 & e^{-1.1547 \mathbf{i} t} \\ |
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\end{bmatrix} |
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</math> |
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Hence, |
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: <math> |
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\dot{\underline{x}} |
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= |
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\begin{bmatrix} |
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-0.2 \mathbf{i} & 0.2 \mathbf{i} & -0.29277 \mathbf{i} & 0.29277 \mathbf{i} \\ |
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0.4 & 0.4 & 0.33806 & 0.33806 \\ |
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0.4 \mathbf{i} & -0.4 \mathbf{i} & 0.58554 \mathbf{i} & 0.58554 \mathbf{i} \\ |
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-0.8 & -0.8 & -0.67621 & 0.67621 \\ |
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\end{bmatrix} |
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\begin{bmatrix} |
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e^{2 \mathbf{i} t} & 0 & 0 & 0 \\ |
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0 & e^{-2 \mathbf{i} t} & 0 & 0 \\ |
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0 & 0 & e^{1.1547 \mathbf{i} t} & 0 \\ |
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0 & 0 & 0 & e^{-1.1547 \mathbf{i} t} \\ |
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\end{bmatrix} |
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\begin{bmatrix} |
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1.25 \mathbf{i} & 0.625 & -0.625 \mathbf{i} & -0.3125 \\ |
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-1.25 \mathbf{i} & 0.625 & 0.625 \mathbf{i} & -0.3125 \\ |
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0.853913 \mathbf{i} & 0.73951 & 0.426956 \mathbf{i} & 0.369755 \\ |
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-0.853913 \mathbf{i} & 0.73951 & -0.426956 \mathbf{i} & 0.369755 \\ |
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\end{bmatrix} |
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\underline{x} |
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</math> |
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so, the matrix exponential can be solved using matrix multiplication. |
Latest revision as of 11:46, 13 December 2009
By Jimmy Apablaza
This problem is described in Page 321-322, Section 7.6 of the A first Course in Differential Equations textbook, 8ED (ISBN 0-534-41878-3).
Problem Statement
Consider the double-pendulum system consisting of a pendulum attached to another pendulum shown in Figure 1.
Assumptions:
- the system oscillates vertically under the influence of gravity.
- the mass of both rod are negligible
- no damping forces act on the system
- positive direction to the right.
The system of differential equations describing the motion is nonlinear
In order to linearize these equations, we assume that the displacements and are small enough so that and . Thus,
Solution
Since our concern is about the motion functions, we will assign the masses and , the rod lenghts and , and gravitational force constants to different variables as follows,
Hence,
Solving for and we obtain,
Therefore,
State Space
Let's plug some numbers. It's known that . In addition, we assume that , , and , so the constants defined previously become,
Hence, the state space matrix is,
Eigenvalues & Eigenvectors
The eigenvalues and eigenvectors are easily obtained with the help of a TI-89 calculator. First, we consider the 's identity matrix,
Once we define the matrix, the eigenvalues are determined by using the eigVi() function,
On the other hand, we use the eigVc() function to find the eigenvectors,
Standard Equation
Now, we plug the eigenvalues and eigenvectors to produce the standar equation,
Matrix Exponential
The matrix exponential is,
where
- ,
and
- ,
so
Again, we can resort to the TI-89 calculator. As it is mentioned above, the matrix exponential is obtained by typing eigVc(a)^-1*a*eigVc(a), where a is the matrix. Thus,
So, the exponential matrix becomes,
where
Hence,
so, the matrix exponential can be solved using matrix multiplication.