Chapter 9    PID Controller Tuning For Dynamic Performance


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The questions will be categorized according to the key concepts concepts in the chapter.

Control Performance Measures Dimensional Analysis
Fine Tuning

 

 

 

 

 

 

 

 

 

 

Check Your Reading

Solidify the Concepts
9.1
Deviation of the controlled variable (CV) from its set point (SP) is an important performance measure because...

Performance Measures 

We chose the CVs using the seven control objective categories.

 

 

the plant could be unsafe for large deviations.

 

 

  

the product quality could be poor for large deviations.

 

 

equipment could be damaged during large deviations.

 

we should never change operating conditions from those specified in the original plant design.

 

 

 

 

 

 

 

 

 

9.2
The rate of change of adjustments to the manipulated variable (MV which is usually a valve) made by a feedback controller...

Performance Measures 

Always plot both CV and MV when monitoring performance.

 

should be very small.

 


 

should be moderate to avoid process upsets.

 

 

  

should be moderate to avoid equipment damage.

 

 

should be rapid enough to return the controlled variable to its set point in a timely manner.

 

 

 

 

 

 

 

 

 

9.3
In the context of controller tuning, "robustness" means...

Performance Measures 

Robustness is a key feature for feedback control.

 

 

 

physical strength.

 

 the ability to achieve reasonable control performance when the process dynamics change.
 

 the ability to keep the control valve from saturating (fully opened or closed).
returning to the set point.

 

 

 

 

 

9.4
When finding the optimum values for tuning constant, we can find KC first, then fix KC and determine TI, and finally, fix the first two and  determine Td.

Fine Tuning 

TRUE     FALSE

 

 

 

 

 

 

 

 

 

 

9.5
Errors in models used for tuning occur...

Fine Tuning 

When we know the cause(s), we can estimate the magnitudes.

 

 

 

due to the linearized approximation.

 

 due to noise in the data used in empirical methods.
 

 due to changes in plant operation, e.g. production rate.
due to round off errors in calculations.

 

 

 

 

 

 

 

 

 

 

 

 

9.6
The Ciancone PID tuning correlations are applicable to processes that...

Fine Tuning 

Every correlations has limits based on the assumptions in the development.

 

 

are exactly first order with dead time.

 

 are overdamped.
 

 are underdamped.
are overdamped and have a monotonic step change.

 

 

 

 

 

 

 

 

 

 

 

9.7
If you knew the model perfectly and you could adjust the manipulated variable without limits, the best PID controller tuning would be...

Fine Tuning 

More about the underlying assumptions and goals of a specific correlation.

 

 

less aggressive than the Ciancone correlations.

 

 more aggressive than the Ciancone correlations.
 

 the same as the Ciancone correlations.