Glen English VK1XX writes:
> Has anyone tried to use a Neural net to control oven tmep, rather than
> the ye olde PID ?
If you believe the marketing, that is why the Nest thermostat is
connected to the cloud.
> IE the algorithm learns from previous beheviour and successfully
> predicts behaviour
Hi Chase
thanks for the email. thanks for the tip on use of logistical classifiers.
Agreed the PID (and variations ) is a seemingly perfect fit , at least
at the top level.. My guess is that the type of disturbance the 'the
system' (affecting, ultimately, the set temperature) (the device)
https://www.electronicdesign.com/analog/whats-all-p-i-d-stuff-anyhow
For all Bob Pease fans: there's a fabulous 9 volume ~1200 page scan of
his columns here:
https://archive.org/details/Bob_Pease_Lab_Notes
The P-I-D article Ben mentions appears in volume 2, starting on page 167.
/tvb
The article link in my post doesn't have valid links to the figures
(Pease hand-drawn schematics), but these links work:
https://web.archive.org/web/20121113202641/https://www.electronicdesign.com/files/29/6131/figure_01.gif
I recall Bob Pease in one of his many "What's all this ...stuff"
columns made a small oven and PID temperature controller that he
claimed kept the temperature within 0.001 degrees or something like
that. This would make machine learning severe overkill. Temp control
is slow enough (and
I will mention that TI has a neural net chip/eval board now for as I recall
$99.
Like so many things maybe it makes sense.
Regards
Paul
WB8TSL
On Tue, Jul 9, 2019 at 11:02 PM Chase Turner wrote:
> Hi Glen,
>
> This is actually something I know a little about.
>
> Neural nets are most useful for
Has anyone tried to use a Neural net to control oven tmep, rather than
the ye olde PID ?
IE the algorithm learns from previous beheviour and successfully
predicts behaviour (or not).
I'm sure there are a few out there proficient with machine learning
algorithms.
Might make a good masters
