The question, dreaded or loved that all engineers face is, “Tell me, what do you do?” As a controls engineer, I fall back to the following example.
Me: Imagine you are driving down the highway and you want to pass someone. What do you do?
Imaginary person: Well I would shift over to the left lane and speed up.
Me: And if they started to go faster as you tried to pass them?
Imaginary person: Well I guess I would speed up some more.
Me: And after you pass them, what then?
Imaginary person: Well I would move back over and slow back to my initial speed(1).
This simple example serves as a starting point for explaining the fundamentals of control algorithms.
- The “objective”: This is the thing we want to control. In this example, it is the speed of our vehicle.
- The input: How we affect the thing we want to control; for an automobile it is by depressing the acceleration pedal that the vehicle is commanded to go faster.
- The feedback: The measurement of how close we are to our desired objective; e.g. are we going fast enough to pass the other car(2).
Everything is Newton’s method…
From the starting point of the automobile example, we can explain that the goal of a control algorithm is to drive the difference between the desired and the actual values to zero. We can expand the driving example to drive our point home.
- Overshoot: When you stamp on the gas and end up going 80 instead of the 75 you needed to pass…
- Fault detection: (Manual drivers only) when you try to hit 80 but are still in 2nd gear…
- Adaptive controls: You drive more carefully in downtown Boston(3) than on a rural highway…
As you could tell, this post is intended to be more light-hearted; however, I do find that thinking about controls problems in a non-technical relatable fashion helps me understand what I am talking about.
“It begins as an idea,
it ends with math(4)“
(1) We know this is an imaginary person since they said they slowed back down after passing.
(2)In this example we actually have an indirect measurement, are we passing the car not the actual speed of the vehicle.
(3) At least I hope you allow more space between drivers when moving about in a rush hour situation.
(4) Frequently, in presentations, I will say “in the end, it all comes down to the math.” While this is true, it lacks the motivation that drives the derivatives.