Hi guys
I know this not quite by the book of control theory, but i am looking into ways to implement an adaptive system onto my PIDF. Lets say (theoretical)
that we dont have equations of state, hence we can't linearize the system around certain operating points. We can only do open-loop step response to estimate a optimal controller. The system is unstable and have complex poles.
With that being said. How would you approach the adaptive system? I know that Asymptotic Properties for LQR/LQG controller works, but i want propose something less complex.
I've tried something so simple as using the step response slope of the system to estimate a time constant (assuming first order), and thereby using abs(time_const-desired_time_constant) as a factor for multiplying the old controller gain.
Do you guys see any other (creative) ways of calculating the adaptive parameters? I have zero time delay. Any (included dump) suggestion are appreciated.

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(I'm cross posting to sci.engr.control in a probably futile attempt to revive that group).
On Sat, 28 Mar 2015 05:56:40 -0500, adrianni wrote:

First, I'm going to make a distinction between "adaptive" and "self- tuning".
"Adaptive", to me, means that the controller adjustment is on-line all the time. I.e., the system is continually watching the plant inputs and outputs, it's adjusting the plant model, and it's updating the controller gains.
"Self-tuning" means that the controller adjustment is a one-time event that happens under operator control: you push the "self-tune" button, the controller generates some stimulus, and watches the plant input and output to generate a controller tuning.
Your step response slope thingie sounds like a self-tuning approach to me, unless you're continually having the system make little extra motions to assist in the self-tuning.
Your approach of looking at the slope of the step response may work in certain limited circumstances. One of the things that strikes me about adaptive and self-tuning control is that the circumstances in which any particular approach works always seems to fit the definition "certain limited circumstance", with the only variable being just how painfully limited "limited" is. So, in your case, it may work.
"Adaptive Control". It provides a good base for understanding this stuff, and they have some material in there on simplified controllers (not to mention ways that you can determine just how limited your particular circumstances are).
Personally, I don't think it's wise to launch into a pursuit of an adaptive controller for a process about which you have no knowledge (it gets back to the limited circumstances -- how do you know your controller will really work?). I wouldn't apply an adaptive controller unless I have a process for which I have a representative model with varying parameters, and I had a pretty good grasp on how those parameters would be varying, and I had determined that a plain old non-adaptive robust controller couldn't do the job.
--
www.wescottdesign.com

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On 3/28/15 2:26 PM, Tim Wescott wrote:

what does the "F" mean in PIDF?
--

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"Imagination is more important than knowledge."
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On 3/28/2015 1:55 PM, robert bristow-johnson wrote:

"proportional + integral + derivative + filter" (PIDF)
Reference:
"Tuning of a PIDF Controller Used With a Highly Oscillating Second Order Process"
--Nasser
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On 3/28/15 4:20 PM, Nasser M. Abbasi wrote:

as if PID isn't already a filter. sounds like some author was trying (and maybe succeeding) at coining a new term that people can associate with that author's name.
--

r b-j snipped-for-privacy@audioimagination.com

"Imagination is more important than knowledge."
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wrote:

I don't follow whatever group had the original post, that's why I'm reverting to Tims post (apologies, Tim I case it's bad form). For the same reason, I'm probably missing some of the information so not sure
Gaining information on the dominant time constant may provide something useful, but stability in a linear system is governed more (in fact totally) by secondary dynamics so any adjustment based on it is likely to be a 'weak handle'. In the real world of process plants that I inhabit, the method you suggest would almost certainly be judged to be a marginal bet. That's not to say that it wouldn't work under some circumstances.
My preferred approach if at all possible is to derive stability compensators from outside the loop.
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