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Here are a few tips:
https://github.com/pidtuner/pidtuner.github.io/blob/master/assets/doc/PID%20Tuner.pdf
It all boils down to having good (noise and perturbation free) step response data.Your data does not show any delay, the process is responding immediately to an input change.
If you want the tool to detect a dead-time, it must be able to see the dead time.
I.e. if your process had a dead-time, it would have a flat output during the dead-time after a change in the input.
Regarding the gains, I show all 5 because some PID implementations use gains, other implementations use times. Just plug in the values that your PID implementation requires. Wikipedia is always your friend.
Maybe this helps:
https://en.wikipedia.org/wiki/PID_controller#Standard_versus_parallel_(ideal)_form
https://github.com/pidtuner/pidtuner.github.io/blob/master/assets/doc/PID%20Tuner.pdf
Hey, happy to hear it worked for you with ease.
As you can imagine, the algorithm is rather complex, but generally speaking, it consists of:- a series of both linear and nonlinear system identification techniques to identify the models based on your data.
- skogestad’s IMC rules for PID tuning based on the models (https://folk.ntnu.no/skoge/publications/2003/tuningPID/more/tuningpaper_reno-2001/tuningpaper_06nov01.pdf)
The PID tuning rules are just given as a tuning starting point. The valuable information are actually the models, you can use any tuning rules over the models to achieve whatever you want with your PID.
Cheers
Hi, have you had a look at the following guide? If so, is it still unclear?
https://github.com/pidtuner/pidtuner.github.io/blob/master/assets/doc/PID%20Tuner.pdfThat is correct, the derivative part is:
PID_D = -(D/Ts) * (yk – ykm1);Just like in here
Hi, the PID algorithm for simulation is similar to this PID implementation:
Glad to hear the PDF solved some of your questions.
Regarding the size of the increments, it should be large enough, such that the output signal can be clearly distinguishable from noise.
In other words, the size of the increments should be large enough such that the output signal displays a clear curve that the pidtuner tool can identify, but not too large so you avoid damaging your hardware.
As a rule of thumb, I always try to split my operating range in 3 to 5 levels.Hi, thank you for using pidtuner.
Looking at your test data, it seems that the step response test has not been done properly. Please look at the following guidelines to make a proper step response:
https://github.com/pidtuner/pidtuner.github.io/blob/master/assets/doc/PID%20Tuner.pdf
Hi, thank you for using pidtuner.
To help us help you better, it would be useful if you share your pidtuner project link with us.
In the meanwhile, take a look at this presentation to check if you have done all the steps correctly:
https://github.com/pidtuner/pidtuner.github.io/blob/master/assets/doc/PID%20Tuner.pdf
Hi,
Thank you for using pidtuner. Looking at your data, it seems that your step test is not done correctly.
First, the input data does not seem correlated to the output data throughout the experiment, see slide 9 (“Common Mistakes …”) of the following presentation:https://github.com/pidtuner/pidtuner.github.io/blob/master/assets/doc/PID%20Tuner.pdf
Second, it seems you are saturating your actuator, since the output looks like it achieves a constant growth speed instead of a natural growth curve. Maybe try a smaller step change.
Hope this information helps,
But the grayed out text precisely says “Use ctrl+V”, have you tried selecting the cell and then hitting ctrl+v ?
Hi,
We are happy you found the FAQ and tool useful. Let us know if you have an specific question in mind or if you need help with an specific data set that you are willing to share.
Best,
Hi,
Yes, it seems you need to modify the gains as you suggest. Also it seems your implementation does not have Derivative action, so when you choose a model in de pidtuner app, make sure is a first order model as to make sure Derivative action is zero.
Take a look to this presentation if you want more confidence that you are doing PID tuning correctly:
https://github.com/pidtuner/pidtuner.github.io/blob/master/assets/doc/PID%20Tuner.pdf
The error is the setpoint (SP) minus the process output (PV). The output column must contain the process output.
Every system (process and PID) has an input and an output. That is why it can be confusing. The PID has as input the error (SP-PV), and the control variable (CV) as output. The process has the CV as input and the PV as output.
What the PID tuner need as “input” is the CV and as “output” the PV. Because it is the input and output of the process. Hope this is clearer.
