[PinguTS]

Coming not from the background of IT but from electrical engineering and industrial control systems, like programmable logic controllers (PLC) and embedded control, I learned that 1990ish.

Fuzzy logic was in favor to the relative new field of neural nets (ML as we know it today). Because from the limitations in industrial control neural nets were too costly. Yes, we had already things like the first i386embedded. But that was way too expansive. Most of the PLCs were based on 16-bit microcontrollers and even those were more on the expansive side.

So if you think commercially in terms of industrial control systems, then Fuzzy Logic was implemented and used. I assume old systems can be found anywhere even today. Remember that in industrial control 20 years is no time.

Today, everybody in industrial control is also about ML. But here again, that is still on the expansive side. Such Nvidia Jetsons do not come for cheap.

[joezydeco]

I spent some time in small industrial controls and we never touched fuzzy logic, but we did a ton of stuff with PID algorithms. Maybe PID was just easier to implement?

[p_l]

It depends on whether your problem maps well to PID, or whether you need to adapt a lot of expert knowledge on a more complex control curve.

[quickthrower2]

PID is alive and well in espresso machines. PID for temperature control is a marketed feature (of cheaper machines: expensive ones you just trust they know what they are doing and have designed it to work at the right temperature)

[p_l]

From what I recall from Fuzzy Logic in University, the main difference is that with PID you give it a setpoint and it reaches and maintains it - while with fuzzy logic you can encode essentially different strategies for different input ranges, something that quite possibly would in turn provide setpoints to PID controllers.