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I am reading about feedforward in control system. And in this lecture, slide 49, the author says that feedforward is common in human systems. Example, walking, playing basketball, driving a car. Could you explain how feedforward is used in walking?

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It's worth noting that there really is no feedforwrd. (Except perhaps for God.) Say you have a camera (or human eyeball) which sees a curve coming. As explained below, the skier or car starts to "pre-turn" based on that information. Note that, quite simply, it's only "forward-feed" in terms of your crappy basic system which only starts to turn when the car literally reaches the turn (perhaps using feelers on the track, say). Note that if you then had a (say) GOS system which knew corners were coming before the cam .. that could be called "forward" info "relative to" the cam. And so on. – Joe Blow Mar 10 at 14:54
It's basically a meaningless, old-fashioned term in the field, lets say. (In the example of a car-camera ... how the hell else would the whole thing work other than a camera looking for corners?! Anything, at all, that we would today even meaningfully describe as a "control system" has "forward" feed. – Joe Blow Mar 10 at 14:58
Is this on-topic here? I get that control systems are often implemented electrically/electronically, but I don't see anything in this question that is specific to electronics or electrical engineering (as per the help center). Would this be a better fit for Eng.SE? – Digital Trauma Mar 11 at 2:15

A good example is driving a car around a curve.

In a pure feedback system, you go straight until the error signal tells you that you're not in the center of the lane anymore, then adjust the steering to compensate.

Humans look ahead and see that a curve is coming up, and actually turn the wheel a little before entering the curve. This pre-compensates for the lag in the car responding.

The other examples you cite are too complex to be useful in illustrating just the feed-forward part of the behavior. There is a lot more to riding a skateboard, for example, than a simple control loop with feed-forward.

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Very good analogy. Motorcycles need to countersteer as well. In that article there's a picture of two motorcycles in speedway racing, and it's plain to see that the rear motorcycle hasn't yet entered the turn, yet is already very much not going straight. – Phil Frost Mar 10 at 12:50
Thank you very much! The example is extremely easy to understand although it doesn't address the original problem. I understand feedforward and feedback much better now. – anhnha Mar 10 at 13:00

I believe the author is making an analogy to human behavior, not human motion.

For example: I'm playing basketball, and I want to score. I know I probably need to dribble towards the basket, avoiding defenders, then throw the ball at the hoop. I know all of this without any feedback: it is a feed-forward system.

A few slides later (50), he writes:

Is Desired output = Output?
Yes if we know the model perfectly!
But, we rarely know a system perfectly (G0 !G, G0 -1 !G-1)

That is, if I knew exactly what all the defenders would do (the model), I could score points in basketball using only a feed-forward system.

Of course that's not exactly true. But I do know a good deal about the model, especially if I'm a good player. I can probably anticipate what the defenders will do more or less, before I make the play. I'll pick my play accordingly.

On the next slide, the author then discusses adding feedback to deal with these unknowns, since most systems don't perfectly know the model.

This is in contrast to purely feedback systems (PID controllers). By incorporating a priori knowledge about the system, and incorporating feedforward into the system, accuracy can be improved and the disadvantages of feeback-only systems can be overcome.

In other words, a basketball player who could not formulate a strategy in advance would not be very good.

That said, from my (rudimentary) understanding of biology, there is a feed-forward component in motion also, with respect to the brain. Check out this TED talk: A robot that runs and swims like a salamander

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Thank you for the detailed answer! – anhnha Mar 10 at 13:59

Could you explain how feedforward is used in walking?

  • When you see an obstacle you make plans to walk around it rather than bloodying your nose or other vital parts
  • When a door is closed you don't bump into it, you slow down and stop then turn the handle
  • When you come to stairs you alter your walking technique rather than falling down the stairs. Ditto getting on and off an escalator
  • Walking on ice - visual feedback of the imminently changing conditions require a more safer walking technique.

There are plenty of examples.

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If you walk forward, and you have no sense of touch and you're blind, as well as muted (and blocked of whatever other senses). Unless you have perfect knowledge of the world model, and of every single consequence a motor cortex action , you're bound to go off track the desired goal (moving forward).

Vision feedback is one thing that can assist you in detecting error (misplacing foot), and correcting the input. Or if you're daredevil, hearing can help you.

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Thank you for help. – anhnha Mar 10 at 13:01

High brain areas in neocortex formulate plans, and feed these plans forward to lower brain areas and spinal cord, which implement them, presumably using inverse models of the motor systems that would be implementing them to generate low level commands. There is, of course, local feedback to keep these plans going right in the presence of surprises and other perturbations.

When I lecture about reflexes (in the context of a physiology course taught to engineers), I take a huge Neuroscience textbook which I've hollowed out to weigh much less than one would think looking at the book, and I toss it to a student. The student, of course, handles it just fine, using spinal reflexes to keep from mishandling the book, none of which involves cortex.

Slightly aside, there is an incredible amount of local feedback at the level of spinal cord, as can be seen in this video of a decerebrate cat walking on a treadmill changing gait as the treadmill speeds up: https://youtu.be/wPiLLplofYw

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