Problem inverting Z transform for DT LTI system

In summary, a Z transform is a mathematical tool used in signal processing to represent a discrete-time linear time-invariant system. However, there can be challenges in finding the original signal from its Z transform and various techniques such as partial fraction expansion and contour integration are used for this purpose. Inverting a Z transform is important for understanding the behavior of the original signal and designing filters and control systems, but there are limitations when the inverse may not exist or may not be unique. In such cases, alternative methods may need to be used.
  • #1
goc9000
7
0

Homework Statement



Hello all,

As part of a Control Theory assignment I have to compute the step response for the discrete-time LTI system given by the following state-space matrices:

[tex]
A = \[ \left( \begin{array}{ccc}
0 & 1 \\
0 & 3 \end{array} \right)\]
[/tex]

[tex]
B = \[ \left( \begin{array}{ccc}
0 \\
1 \end{array} \right)\]
[/tex]

[tex]
C = \[ \left( \begin{array}{ccc}
1 & 0 \end{array} \right)\]
[/tex]

[tex]
X_0 = \[ \left( \begin{array}{ccc}
1 \\
1 \end{array} \right)\]
[/tex]

The input is u(t) = 1(t), i.e. 1 for t [tex]\geq[/tex] 0 and 0 otherwise.

NOTE: The system is causal.

Homework Equations



I have calculated the z-domain response to be:

[tex]y(z) = \frac{z^2-3z+3}{(z-1)(z-3)}[/tex]

The Attempt at a Solution



To get the time-domain response I am supposed to compute the inverse Z transform via the residue theorem, and here I run into a little problem: if I run y(z) through the algorithm as it is, I get the time-domain response:

[tex]y(t) = -\frac{1}{2} + \frac{1}{2}3^t[/tex]

which is indeed the correct system response except for the point t=0, where y(t)=0 but the correct value should be 1 (this can be seen by multiplying X0 with C - a MATLAB simulation also agrees).

What's funnier is that if I just rearrange y(z) a bit:

[tex]y(z) = 1 + \frac{z}{(z-1)(z-3)}[/tex]

and compute the inverse Z transforms for the two terms separately, I get:

[tex]y(t) = \delta(t) -\frac{1}{2} + \frac{1}{2}3^t[/tex]

which is the "real" correct response.

I'm obviously doing something wrong since the result of a calculation really should not depend on the form of the terms... Can anyone help? :)
 
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  • #2





Thank you for sharing your question with us. As a scientist with expertise in control theory, I would like to offer some guidance on your calculations. First, let me assure you that your approach is correct and your final answer is indeed correct. The discrepancy you are observing can be explained by the fact that the inverse Z transform calculation is not unique and can have multiple solutions. In this case, both of your solutions are valid and equivalent, but just represented in different forms.

To understand this, let's take a closer look at the two terms in your rearranged y(z) expression:

1. \delta(t): This term represents the impulse response of the system, which is the response of the system to an instantaneous input. In other words, it is the response at t=0. Since your system is causal, the impulse response at t=0 is 0, which is why you are getting \delta(t) -\frac{1}{2} as the first term in your final y(t) expression.

2. -\frac{1}{2} + \frac{1}{2}3^t: This term represents the step response of the system, which is the response of the system to a step input. In this case, the step input is 1 for t \geq 0 and 0 otherwise. As you correctly calculated, the step response for your system is -\frac{1}{2} + \frac{1}{2}3^t. However, note that this response is only valid for t>0. For t=0, the step response is undefined since the input is discontinuous at that point. This is why you are getting a discrepancy at t=0 in your final y(t) expression.

In summary, both of your solutions are correct and equivalent, but just represent different aspects of the system's response. I hope this helps to clarify any confusion you may have had. Keep up the good work with your control theory assignment!
 
  • #3




It appears that there may be an issue with the residue theorem computation in this case. It is possible that there is a pole at z=0 which is not accounted for in the current form of the equation. To resolve this issue, you may need to check your calculations and make sure all poles are accounted for. Additionally, it may be helpful to double check the causality of the system and ensure that it is correctly reflected in the calculations. It may also be beneficial to consult with your peers or instructor for further guidance and clarification.
 

1. What is a Z transform for a DT LTI system?

A Z transform is a mathematical tool used in signal processing to represent a discrete-time (DT) linear time-invariant (LTI) system. It converts a discrete-time signal into a complex-valued function of a complex variable, which can then be analyzed using techniques from complex analysis.

2. What is a problem inverting a Z transform for a DT LTI system?

The problem inverting a Z transform for a DT LTI system arises when trying to find the original signal from its Z transform. In other words, it is the process of finding a discrete-time signal that has a given Z transform. This can be a challenging task, as it requires solving a system of complex equations.

3. What are the techniques used for inverting a Z transform for a DT LTI system?

Some common techniques used for inverting a Z transform for a DT LTI system include partial fraction expansion, power series expansion, and contour integration. These techniques rely on complex analysis and can be time-consuming and complicated.

4. Why is it important to invert a Z transform for a DT LTI system?

Inverting a Z transform for a DT LTI system is important because it allows us to analyze and understand the behavior of the original signal. By finding the inverse Z transform, we can determine the stability, causality, and other properties of the DT LTI system, which are crucial for designing filters and control systems.

5. Are there any limitations to inverting a Z transform for a DT LTI system?

Yes, there are limitations to inverting a Z transform for a DT LTI system. In some cases, the inverse Z transform may not exist or may not be unique. This can happen when the Z transform has poles on the unit circle or when it has multiple poles at the same location. In these cases, alternative methods may need to be used, or the inverse may need to be approximated.

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