How Do Settling Time and Overshoot Change as System Gain Increases to Infinity?

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In summary, the conversation discusses finding the settling time and overshoot of a transfer function with a varying parameter, m, approaching infinity. The root locus method is suggested as a possible approach, but it is noted that the response becomes zero as m approaches infinity. The conversation then explores simplifying the equation and using the root locus method to find the roots of the transfer function.
  • #1
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1. Homework Statement + the attempt at solution
I have the next transfer function:

[tex]H(s)=\frac{P(s)}{1+C(s)P(s)}[/tex]

where [tex]P(s)=\frac{20}{(s^2-2s+9)(s+100)}[/tex]

[tex] C(s)=m(s+40)[/tex]

Now I want to find the settling time and overshoot of [tex]H(s)[/tex] as [tex]m\rightarrow \infty[/tex] to whithin 5 percent accuracy.

Now what I thought when [tex]m\rightarrow \infty[/tex] [tex]H(s)\approx \frac{1}{C(s)}[/tex].

So basically in this case the quadratic equation (in the notation of next webpage:
http://wikis.lib.ncsu.edu/index.php/Second_Order_Dynamics) is:

[tex]s^2+(-2s+20ms)+(9+800m)[/tex]

Is this right or am I just rambling nonsense here, I am lost here.



Homework Equations


I know that when we have the Quadratic ploynomial in the denominator of [tex]G(s)=P(s)C(s)[/tex] s.t:
[tex] s^2+2\zeta \omega_n s +\omega_n ^2[/tex]

then the settling time is given by:

[tex]t_s \approx \frac{3}{\zeta \omega_n}[/tex]

and the overshoot is given by:

[tex] \sigma = exp(\frac{-\zeta \pi}{\sqrt{1-\zeta^2}})[/tex]

Any hints or advice are welcomed and much appreciated.

Thanks.
 
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  • #2
Are you familiar with the root locus method? It describes the path the roots take when a single parameter, like m, is varied. I would need to do a little review before giving a better answer but maybe this will get you started.
 
  • #3
Yes I know about the RL.

I am not sure how to calculate the overshoot and settling time here, though I know that I need to look at the Bode graph of [tex]\frac{1}{m(s+40)}[/tex]

And I know that the frequency that the asymptote to the the magnitude of the above expression intersects the [tex]\omega[/tex] axis is given by: [tex]\omega= 40[/tex].

Other than that, I am not sure how to procceed, any advice?
 
  • #4
My reaction is to agree with you that as m → ∞, H(s) = 1/C(S) = 1/m(s+40).

The impulse response to this H(s) is simply (1/m)exp(-40t). The step response is simply (1/m)[1 - exp(-40t)]. In neither case is there any overshoot. So I am as confused as you ... :smile:
 
  • #5
And what of the settling time of 1/C(s)?

Thank you for your help.
 
  • #6
MathematicalPhysicist said:
And what of the settling time of 1/C(s)?

Thank you for your help.

Since the output is an exponential decay you can compute settling time depending on your definition of "settling time". For example, if the input is a step function, and "settling time" ts is defined as 95% of "final" value, then you solve for ts from 1 - exp(-40ts) = 0.95.
 
  • #7
OK, thanks.

Then the overshoot is zero.
 
  • #8
The problem with m→∞ is that the response goes to zero. So you can't let m→∞. Maybe you can say m becomes large enough that it dominates the response. Then I do agree with what you have been saying. You can call the (s+100) pole insignificant as I think you did or you could do this, which is another way to deal with these sorts of boundary case problems:

[itex]0=1+C(s)P(s)=s^3+98s^2+(20m-191)s+(900+800m)[/itex]

Making m large can simplify this by making most terms too small to be counted. Dividing by m yields this:

[itex]0=\frac{1}{m}(s^3+98s^2-191s+900)+20s+800\approx s+40[/itex]

This means you have a single pole response as you found.

Your root equation can be written in the standard form with the parameter m in the right place for root locus:

[itex]1+C(s)P(s)=1+m\frac{20(s+40)}{(s^2-2s+9)(s+100)}=1+mQ(s)[/itex]

The root locus method says as m begins at 0 and approaches ∞, the roots of this equation begin at the poles of Q(s) and end at the zeroes of Q(s). Q(s) has two zeroes at ∞ and one zero at -40. It has three poles, one at -100 and two complex conjugate ones. The conclusion from root locus is that with m→∞, there will be two roots at ∞ and one at -40. The finite root is (s+40) as found above.
 
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Related to How Do Settling Time and Overshoot Change as System Gain Increases to Infinity?

1. What is settling time?

Settling time is the time it takes for a system to reach and stay within a specified range of its final value after a disturbance or change in input.

2. How is settling time measured?

Settling time is typically measured by observing the system's response to a step input and determining the time it takes for the output to settle within a certain percentage of the final value.

3. What causes overshoot?

Overshoot occurs when a system's response to a change in input goes beyond its final value before eventually settling within the specified range. This can be caused by factors such as system instability, high gain, or inadequate damping.

4. How is overshoot calculated?

Overshoot is typically calculated as a percentage of the final value, with a larger percentage indicating a greater amount of overshoot. It can also be calculated as the difference between the maximum output value and the final value.

5. How can settling time and overshoot be reduced?

To reduce settling time and overshoot, factors such as system design, controller parameters, and feedback control can be adjusted. Other methods include using filters, predicting system behavior, and implementing advanced control techniques.

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