Designing a Cruise Control System Controller with Root Locus Method | Coursework

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Discussion Overview

The discussion revolves around the design of a controller for a Cruise Control System using the Root Locus method. Participants express challenges in understanding the method, its application, and the implications of various design choices on system stability and performance metrics such as rise time and overshoot.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Homework-related
  • Mathematical reasoning

Main Points Raised

  • Some participants express confusion about how many poles or zeros need to be moved to achieve system stability.
  • There is a discussion on whether to move poles, zeros, or both, with some suggesting that adding zeros can improve stability.
  • Participants question the significance of the dotted lines and semicircle in the context of rise time and overshoot, seeking clarification on their implications.
  • One participant notes that while a specific pole location (-0.4) is suggested, they struggle to understand how to select an appropriate point that meets the desired performance criteria.
  • There is a mention of discrepancies between theoretical calculations and MATLAB simulations regarding rise time and overshoot, with participants debating the accuracy of the results.
  • Some participants inquire about the nature of overshoot in a first-order system, indicating uncertainty about the calculations presented in the tutorial they referenced.
  • One participant confirms that the rise time observed in MATLAB does not align with expectations, prompting further investigation into potential errors in the design or calculations.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the effectiveness of the proposed pole location or the accuracy of the rise time and overshoot calculations. Multiple competing views remain regarding the interpretation of the Root Locus method and its application to the problem at hand.

Contextual Notes

Participants express uncertainty about the assumptions underlying their calculations and the definitions of stability and performance metrics. There are unresolved questions about the relationship between theoretical predictions and practical outcomes as observed in simulations.

  • #31
Altairs said:
Does that mean that the terms risetime, settling time and overshoot etc have no meaning at all for a pure derivative controller ? But when I think again I get confused that there should be some settling time formula or for overshoot etc. If yes then what is it ?

So what is going to be steady state value in case of pure derivative controller ? Zero, always ?
The settling time is zero.
The ss value can be obtained from the final value theorem. The settling time is the time when response attains 1% or 2% of its final value. In a negative exponent exponential, what is the time when this happens?
 
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  • #32
Altairs said:
And what about PID controller how do I find rise time etc for a PID controller...It has to has some...

Obtain the time response and verify how long does it take from 10% to 90% of ss.
 
  • #33
CEL said:
In a negative exponent exponential, what is the time when this happens?

Indefinite ?
 
  • #34
Altairs said:
Indefinite ?

When isKe^{-\alpha t} equal to 0.01K or 0.02K?
 
  • #35
CEL said:
When isKe^{-\alpha t} equal to 0.01K or 0.02K?

\frac{-ln(0.01)}{\alpha}
 
  • #36
CEL said:
Obtain the time response and verify how long does it take from 10% to 90% of ss.

I have got the steady state value but how do I get the time response ? Laplace Transform ? Isn't there some shorter method ? This is because I have got a zero as well in the PI controller so the general formulae doesn't work..Any approximation ? I don't want to go for any tedious method...
 
  • #37
Altairs said:
I have got the steady state value but how do I get the time response ? Laplace Transform ? Isn't there some shorter method ? This is because I have got a zero as well in the PI controller so the general formulae doesn't work..Any approximation ? I don't want to go for any tedious method...

You must take the inverse tarnsform of the response Y(s). Don't forget that the transform of the step is 1/s, so the s in the denominator cancels the s in the numerator.
 

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