Draw Trajectories for Autonomous DE: Where to Begin?

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In summary: What is the full solution to the DE?The full solution to the DE is $e^{t \mathbf{A}} \mathbf{x}_{0}$.
  • #1
onie mti
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0
when you are asked to draw a trajectory for a an autonomous DE, where does one begin
eg
given the matrix A=
1 0
0 -1


they say find e^tA then draw the trajectories. I know how to find e^tA but i cannot draw
 
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  • #2
Well, go ahead and compute $e^{t \mathbf{A}}$. You'll have some initial condition $\mathbf{x}_{0}$. Your solution to the DE $ \dot{ \mathbf{x}}=A \mathbf{x}$ is then $e^{t \mathbf{A}} \mathbf{x}_{0}$. Go ahead and perform the matrix multiplication $e^{t \mathbf{A}} \mathbf{x}_{0}$ and see what you get.
 
  • #3
Ackbach said:
Well, go ahead and compute $e^{t \mathbf{A}}$. You'll have some initial condition $\mathbf{x}_{0}$. Your solution to the DE $ \dot{ \mathbf{x}}=A \mathbf{x}$ is then $e^{t \mathbf{A}} \mathbf{x}_{0}$. Go ahead and perform the matrix multiplication $e^{t \mathbf{A}} \mathbf{x}_{0}$ and see what you get.

My eigenvalues were 2 and 1
Eigenvector associated with λ_1=2 is ■(0@1) and
λ_1= Is ■(1@0)
Where x(t) = c(1)e^(2t) ■(0@1) + c(2)e^t ■(1@0)

Now solving for e^tA
x_1(0)= ■(1@0) = c(1)e^2t ■(0@1) + c(2) e^t ■(1@0)
Where c(1)= 0 and c(2)= 1

Then for x_2(0), c(1)= 1 and c(2) = 0
Such that, x_1(t)= c(2) ■(1@0)
x_2(t) = e^2t ■(0@1)
Therefore e^tA is: ■(c(2) ■(1@0) @e^2t ■(0@1))
I still do not understand how to do the trajectories
 
  • #4
Hmm. You might want to check your calculations. With a diagonal matrix, the eigenvalues are simply the values on the diagonal. In this case, you get $\lambda= \pm 1$; the eigenvector for $\lambda=1$ is $\begin{bmatrix}1 \\ 0 \end{bmatrix}$, and the eigenvector corresponding to $\lambda=-1$ is $\begin{bmatrix}0 \\ 1 \end{bmatrix}$. As the matrix is already diagonal, you can exponentiate it fairly easily:
$$e^{t \mathbf{A}}= \begin{bmatrix} e^{t} &0 \\ 0 &e^{-t} \end{bmatrix}.$$
What is your initial condition?
 
  • #5
Ackbach said:
Hmm. You might want to check your calculations. With a diagonal matrix, the eigenvalues are simply the values on the diagonal. In this case, you get $\lambda= \pm 1$; the eigenvector for $\lambda=1$ is $\begin{bmatrix}1 \\ 0 \end{bmatrix}$, and the eigenvector corresponding to $\lambda=-1$ is $\begin{bmatrix}0 \\ 1 \end{bmatrix}$. As the matrix is already diagonal, you can exponentiate it fairly easily:
$$e^{t \mathbf{A}}= \begin{bmatrix} e^{t} &0 \\ 0 &e^{-t} \end{bmatrix}.$$
What is your initial condition?

I was not given any initial condition
 
  • #6
onie mti said:
I was not given any initial condition

Ok, that's fine. Let's call the initial condition something arbitrary, then: $\begin{bmatrix}x_0 \\ y_0 \end{bmatrix}$. What is the full solution to the DE?
 

FAQ: Draw Trajectories for Autonomous DE: Where to Begin?

What is the purpose of drawing trajectories for autonomous DE?

The purpose of drawing trajectories for autonomous DE is to visualize the path that an autonomous system will take in a given environment. This allows scientists and engineers to analyze and optimize the system's behavior and performance.

What factors should be considered when drawing trajectories for autonomous DE?

Several factors should be considered when drawing trajectories for autonomous DE, such as the system's dynamics, constraints, and environment. Other factors may include the system's sensors, control algorithms, and communication protocols.

How do you begin drawing trajectories for autonomous DE?

The first step in drawing trajectories for autonomous DE is to define the system's dynamics and constraints. This can be done using mathematical equations or physical models. Next, the environment and any external factors should be taken into account. Finally, the trajectories can be calculated using simulation software or by hand.

What are some common challenges when drawing trajectories for autonomous DE?

Some common challenges when drawing trajectories for autonomous DE include accurately representing the system's dynamics and accounting for uncertainties in the environment. Other challenges may include balancing the trade-off between performance and safety, and incorporating complex control algorithms into the trajectory planning process.

How can drawing trajectories for autonomous DE benefit real-world applications?

Drawing trajectories for autonomous DE can benefit real-world applications by allowing for more efficient and effective autonomous systems. By visualizing and analyzing the trajectories, scientists and engineers can make improvements to the system's design and performance. This can lead to safer and more reliable autonomous systems for various applications, such as self-driving cars and drones.

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