At university, my control engineering courses are focused on a more theoretical approach, but the main message from our professors was clear: When designing a feedback controller (PID, H-infinity, MPC,...), always prove stability of the controlled system, check the robustness etc., and of course, always have an appropriate (identified) model of the plant. Essentially we were shown what could happen with a badly chosen controller and that a solid theoretical analysis is a must-have to avoid that.

So over the years I talked to electrical and mechanical engineers without that formal background who worked on controlled systems (but rather small systems that could fail without people getting hurt), and many of them never used the "theoretical tools" (some even didn't know what "Robustness" means) we were told to use. The electrical engineers espacially, simulated the system and if they were satisfied with the results they went with it. Even in some non-control-engineering text-books and a Udacity course a "trial of parameters until the behaviour seems okay" - approach was suggested for PID design, which "horrified" me (Note: even something like Ziegler-Nichols was very "discouraged" by one of our professors)

The formal approaches seem to be important, but of course, the model is always imperfect (and are often costly to get) and often it worked in theory, but still had to be adjusted. Furthermore, I found it difficult to judge if a certain gain & phase margin actually is okay, or the control law of a sliding mode controller really stays small enough. Meaning you always have to see how it behaves in reality and do some iterations. But if you only do trial and error, you might have a system that works - until it doesn't.

So my question is: What is the most pragmatic approach here? Do some of you have some experience with control design and can you shed some light on this?

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    $\begingroup$ Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. $\endgroup$
    – Community Bot
    Jun 15 at 12:47
  • $\begingroup$ "What is the most pragmatic approach here?" The one you have the budget for that meets the needs. If you're a hamburger plant you probably don't want to invest millions and millions of research dollars perfectly modelling the entire factory. But if you're a fighter jet you might. I'm guessing it was a lot easier for you to find people who work on things like hamburger plants and zero chance to work to speak to people who work on fighter jets. It's easier to get a new batch of hamburgers to re-test than it is a new prototype plane. $\endgroup$
    – DKNguyen
    Jun 15 at 18:45
  • $\begingroup$ When we have MIMO systems and not just SISO systems, one really needs these advanced methods. PID alone is not enough for MIMO? $\endgroup$
    – Nasser
    Aug 2 at 23:04

1 Answer 1


Here are some perspectives from someone who was taught rigorous control systems theory and then spent 34 years working in high tech.

Imagine you have a programmable PID controller box with which you intend to enforce setpoint control on an industrial process of some sort. It is possible for an untrained person through hit-and-miss fiddling about with the control system knobs to find the sweet spot where you get what you want and the process does not run out of control, especially if you already have some experience doing this on similar systems.

But the basic problem with this approach is the minute the system goes berserk and starts your factory on fire, you won't have any clue as to why it went wrong and you'll have no tools to find out why except fiddling about, which is something that line supervisors and plant managers generally have little patience for.

This is why controls system design always and forever begins with a mathematical model of the "plant" and ends with a comparison between the actual behavior of the plant and the predictions of the model. If the model doesn't match reality, you start over and add more physics to the model until it does. And you don't hook up a control loop until you have a good model.

  • $\begingroup$ Well, always and forever is often a function of manager knowledge and budget. While i agree a formal method should be the correct way, in my experience my coworkers and bosses preferred fiddling to actually knowing what they‘re doing, regardless if fiddling ended up costing more time/money in the long run anyways… $\endgroup$ Jun 18 at 16:28
  • $\begingroup$ @DrMrstheMonarch, In the business I was once in, one minute of downtime in one of the factories cost my employer $1350 and aimless fiddling was officially frowned upon. This meant that if I could increase their uptime by two minutes, it would pay to send me from oregon to puerto rico, ireland, singapore, boise or san diego for a week to debug an out-of-control production line. NO FIDDLING!!! $\endgroup$ Jun 18 at 23:13
  • $\begingroup$ i agree with you entirely, unfortunately a lot of employers don‘t ;p $\endgroup$ Jun 18 at 23:48
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    $\begingroup$ @DrMrstheMonarch, luckily for me I am now a recovering ex-engineer. there's a 12-step program for that but unfortunately it's not very effective. $\endgroup$ Jun 19 at 0:02

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