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Proportional-Integral-Derivative (PID) controllers

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Re: Proportional-Integral-Derivative (PID) controllers

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post #3

The fascination of programmer types with classical control and estimation topics is endlessly interesting as someone who studied control and estimation and hangs out here for interest in the programming. For me it was surprising to see that JEPA is a model predictive control algorithm it an almost literal sense; I guess I’m happy to have studied what I chose when I was 18.

Yeah, kind of hilarious to me that this was posted here. I suppose if you’ve never encountered control systems at all before they are quite simple, elegant, and cool, but I’m surprised any technical person hasn’t come across them at some point.

https://xkcd.com/1053/

Re: Proportional-Integral-Derivative (PID) controllers

#13
post #3

The fascination of programmer types with classical control and estimation topics is endlessly interesting as someone who studied control and estimation and hangs out here for interest in the programming. For me it was surprising to see that JEPA is a model predictive control algorithm it an almost literal sense; I guess I’m happy to have studied what I chose when I was 18.

This classic programming text book discusses computational analogs of the "signals" in signal-processing systems.

https://mitp-content-server.mit.edu/books/content/sectbyfn/b...

Re: Proportional-Integral-Derivative (PID) controllers

#15
post #7
post #3

The fascination of programmer types with classical control and estimation topics is endlessly interesting as someone who studied control and estimation and hangs out here for interest in the programming. For me it was surprising to see that JEPA is a model predictive control algorithm it an almost literal sense; I guess I’m happy to have studied what I chose when I was 18.

I signed up for one of the first MOOCs ever, about self driving cars by Sebastian Thrun, and of course PID was part of the curriculum. I think that PID hits a certain sweet spot between cleverness, ease of implementation and practical utility that makes it catnip for the typical programmer's mind. I liked it so much that when we had to implement it, I downloaded an open source driving simulator to see it work there i…

Whatever happened to this guy?

Sounds like he made a bag with the first AI craze and retired.

Re: Proportional-Integral-Derivative (PID) controllers

#16
post #10

I used it in metal detector (direct frequency measurement kind). It works really well. I (and you probably too) half assed pid controllers before you even know what it is. But it makes perfect sense. Proportional part reacts to the acute difference, derivative adjusts it when your controller is already going right direction to limit overshoot, and integral part improves cases when the difference is small but persist…

Almost always a good analysis will find a control strategy which performs better than PID...

But the benefit of PID is it is fairly easy to tune and works in a really wide range of situations.

Re: Proportional-Integral-Derivative (PID) controllers

#18
post #9
post #6

Earlier quoted context omitted.

Yeah, kind of hilarious to me that this was posted here. I suppose if you’ve never encountered control systems at all before they are quite simple, elegant, and cool, but I’m surprised any technical person hasn’t come across them at some point.

I think CS degrees are a bit light on classical theory in the modern day. In Australia CS degrees are what they say on the tin, but in America it seems almost as if CS degrees are anywhere from cybernetics to pure software development

Interesting generalization; that’s almost the opposite of my experience.

A common hiring anecdote we share with people outside tech is literally: “A CS degree doesn’t teach you how to code.”

For me, ~25 years ago in the UC system, it was all math/science/theory-oriented. Some C++/Java that was introduced to get you through all that theory. Learning how to code/actual software engineering comes with practical experience.

Re: Proportional-Integral-Derivative (PID) controllers

#19
PIDs are great but notoriously hard to tune. They require deep insight into the underlying physical phenomena to get right. They are also rather rigid and cannot adjust well to a changing environment (temperature and humidity can fluctuate dramatically between summer and winter in some climates).

Of course, no one tunes them by hand anymore for these reasons, relying instead on optimization techniques like particle swarm to find the best set of coefficients for a given steady state condition. Eventually, I suspect we will replace most PIDs with a small neural network for almost all industrial applications (a handful of nodes is sufficient). The neural network is also easier to adapt to changing conditions.

Re: Proportional-Integral-Derivative (PID) controllers

#20
post #9
post #6

Earlier quoted context omitted.

Yeah, kind of hilarious to me that this was posted here. I suppose if you’ve never encountered control systems at all before they are quite simple, elegant, and cool, but I’m surprised any technical person hasn’t come across them at some point.

I think CS degrees are a bit light on classical theory in the modern day. In Australia CS degrees are what they say on the tin, but in America it seems almost as if CS degrees are anywhere from cybernetics to pure software development

That hasn’t been my experience in the US, either personally or from talking to others who took CS degrees.

Keep in mind that plenty of people on HN and in the industry did not take CS degrees in college. We did learn about PIDs, if briefly.

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