[regularfry]

My memory of learning control theory at university was learning some super complicated stuff that was applicable to 99% of control problems. PID controllers, which are good for probably 95% of control problems, were effectively "an exercise for the reader". So trivial compared to the broader theory we were studying that nobody even thought to mention them. The expectation seemed to be that when you needed them, they'd just drop out of the maths and they'd need no further explanation.

We'd already done a form of proportional control with op-amps. It would have been enormously helpful to start control theory with discrete PI and PID to give us a practical grounding and something we could actually use before leaping off into the wider theory, but that's not how academia works...

[HeyLaughingBoy]

This problem persists even in applied classes. I was taking a set of courses in Mechatronics for engineers who were already working in in industry. We went deep into the theory of various types of controls but when one of the students (an engineer with probably 20+ years of experience) asked about PID, it was dismissed as a "special case" of (I think) a Phase Lead control.

Happily the guy teaching the lab portion of the class was himself an experienced controls engineer who actually knew how to use the math to accomplish something useful. We learned far more from him than from the lecture classes.

[Filligree]

As someone who's only worked with PID controllers, do you have any pointers to the more complicated stuff you're thinking about? A wikipedia article maybe?

[regularfry]

It's been a while, but I remember https://en.wikibooks.org/wiki/Control_Systems/MIMO_Systems#S... as a fair example. State-space representation is very powerful, and totally unnecessary for PID.

[nuclearnice1]

Try Model predictive control (MPC) and linear quadratic regulator (LQR)