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 instead of the simpler python environment we were using.
It’s very intuitively appealing. We like it at my university for teaching first years how to build a line following robot. It’s one of the first times you can get students to really get that “ah” moment when they realise what they can do with code—it can affect the real world!
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
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 for long time. Learn them and use them, they're good tool.
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 instead of the simpler python environment we were using.
It’s very intuitively appealing. We like it at my university for teaching first years how to build a line following robot. It’s one of the first times you can get students to really get that “ah” moment when they realise what they can do with code—it can affect the real world!
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
https://xkcd.com/1053/
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 for long time. Learn them and use them, they're good tool.
Honest question: are wiki links to any technical topic post worthy now?
Obligatory link to PID without a PhD: https://www.wescottdesign.com/articles/pid/pidWithoutAPhd.pd...
thank you!