[Dprglist] PID

[markus]

I found this a great demo:
https://www.youtube.com/watch?v=fusr9eTceEo

On Thu, 24 Sep 2020 17:03:30 -0500
Karim Virani via DPRGlist <dprglist at lists.dprg.org> wrote:

> I was mostly silent on that call - there were plenty of experiences
> shared on the subject. I'll say my team(s) got away with PD control
> for years. As far back as FLL. We never needed integral until 2 years
> ago when we had a rolling "foot" that raised the angle of the robot
> through a wide range of back pressure. Then we spent a good month
> learning about different anti-windup options. I still think of the
> integral as the trickiest of the terms and the least useful - until
> you run into that specific case where it is vital.
> 
> Back in our FLL days we built a PID trainer. A single gear motor
> driving a sweeping arm in front of a marked "gauge." By being
> dedicated, tuned with rotation sensors, and off-robot it allowed more
> team members to play around with values and develop an intuitive
> sense of the dynamics. Then we'd change the gearing from the motor or
> the load on the arm and see how the dynamics change. We should do
> that again for our incoming FTC rookies.
> 
> It's not that hard to estimate what PID values you might expect to
> start with, but the tuning process can go pretty rapidly once you get
> used to it
> - and then the starting values don't matter that much - the actual
> values arrived at through experimentation reign supreme. Setting
> yourself up for an efficient tuning process helps a lot. Prioritize
> feedback and real-time adjustment without having to recompile your
> code unless you determine your PID controller needs functional
> improvement.
> 
> On Thu, Sep 24, 2020 at 4:40 PM Ezra Christensen via DPRGlist <
> dprglist at lists.dprg.org> wrote:  
> 
> > Patrick - do you have anyone on your team that is versed in ML? I'm
> > wondering if anyone has run an auto-tuning ML algo to come up with
> > coefficients, including possibly non-constant coefficients. The
> > trial/error approach seems tedious and prone to "close enough"
> > calls from humans bored of optimizing the three.
> >
> > My FLL team built a calibrate sequence for i they would push before
> > a run. They found the motors and tires weren't consistent and the
> > bot would start driving better after X distance. Their hypotheses
> > was that the total error had to become sufficient to let the
> > integral start doing it's part to account for any mechanical drift
> > of how the bot was feeling at that moment (EV3s aren't super
> > consistent, even with the same parts).
> >
> >
> > Ezra
> >
> > On Thu, Sep 24, 2020 at 4:23 PM Patrick R. Michaud via DPRGlist <  
> > dprglist at lists.dprg.org> wrote:  
> >  
> >> While I've always been able to make good use of P-controllers,
> >> full PID tuning was a bit of a black box for me, even after
> >> reading lots of other resources (including the Wikipedia article).
> >>
> >> This past season our 7172 team needed much better control of their
> >> elevator -- P-control wasn't at all sufficient -- and the trick
> >> for us was to have the robot display the real-time contributions
> >> of P, I, and D to the result.  That really enabled the group to
> >> see how they could improve the I and D terms to get a more
> >> consistent result.
> >>
> >> I hope any videos/recordings of Tuesday's session are posted soon,
> >> I'd really like to see what was discussed.
> >>
> >> Pm
> >>
> >>
> >> On Thu, Sep 24, 2020 at 03:40:42PM -0500, David Anderson via
> >> DPRGlist wrote:  
> >> > Howdy DPRG,
> >> >
> >> > As per our discussion at RBNO Tuesday evening on PID tuning,
> >> > check out:
> >> >
> >> > https://en.wikipedia.org/wiki/PID_controller
> >> >
> >> > and particularly the cool animation of adjusting P,I,D values in
> >> > the  
> >> "Manual  
> >> > tuning" section about half way down.
> >> >
> >> > There's also a useful "for dummies" page at:
> >> >
> >> > https://www.csimn.com/CSI_pages/PIDforDummies.html
> >> >
> >> > cheers
> >> >
> >> > dpa
> >> >
> >> >
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> >
> > --
> > Ezra C Christensen
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