[From Adam Matic 2014.02.03.0033 CET]
Rick Marken (2014.01.27.1240)
2, In this chapter Bill discusses two approaches to explaining control -- two versions of control theory: Modern Control Theory (MCT) and Classical Control Theory (which is what PCT is). Bill says that MCT has been a "formidable obstacle to the acceptance of PCT". Based on your reading of the section on MCT why do you think this might have been the case? That is, why might the MCT approach to explaining control have been an obstacle to acceptance of PCT?
AM: Perhaps it's because PCT seems very simple compared to MCT, and it's 'common knowledge' that behavior is very complex, so it couldn't be explained by simple negative feedback loops. Although, from my experience, once you get to multilevel structures, things quickly stop being simple.
Another obstacle is, of course, the fact that MCT (with some exceptions) refers to the output variable as the controlled variable. It's a different perspective that often results in very different designs of control systems. While PCT is more 'from the view of the control system' perspective, MCT takes an external, engineer-designer perspective.
3. On p. 9, paragraph 2 Bill says that "A negative feedback controller...doesn't have to know what is causing the speed [controlled variable] to change." The rest of the paragraph goes on to explain why this is so and why this distinguishes the PCT (classical) controller from the MCT controller. In your own words can you describe how this description of the PCT model of control differs from the MCT model.
AM:
The main difference is that in PCT there is no attempt to pre-calculate the future state of the controlled variable, either input or output, from some other perceived variables.
Related to the feedforward discussion, from what I understand, not all feedforward is prediction using formulas and complex mathematics. Some types of hybrid feedforward and feedback systems are constructed so that feedforward improves control,but this is only possible when the 'plant' is known. It might be that human memory works similar to these feedforward components. When we develop a skill, it might be that we use something 'more' than pure negative feedback (not something more then PCT, though).
I've been reading some flyball catching experiments, this one seems relevant:
The effects of baseball experience on movement initiation in catching fly balls (Oudejans, et all 1997) <http://dare2.ubvu.vu.nl/bitstream/handle/1871/28892/113994.pdf>http://dare2.ubvu.vu.nl/bitstream/handle/1871/28892/113994.pdf
Abstract:
Previous research has shown that skilled athletes are able to respond faster than novices to skill-specific information. The aim of this study was to ascertain whether expert outfielders are faster than non-experts in acting on information about the flight of a fly ball. It was hypothesized that expert outfielders are better attuned to this information; as a result, faster and more accurate responses were expected. This hypothesis was tested by having non-expert and expert outfielders judge, as quickly as possible, where a ball would land in the front- behind dimension (perceptual condition) and, in another condition, to attempt to catch such balls (catching
condition). *** The results of the perceptual condition do not support the hypothesis that expert outfielders are more sensitive to ball flight information than non-experts, *** but the results of the catching condition reveal that experts are more likely to initiate locomotion in the correct direction.
What we can see is that skilled catchers are no better than unskilled ones in *predicting* where the ball will fall from initial flight information. That would be expected if humans were analyse-compute-act systems. Improving a skill would mean improving the ability to predict the end point from initial conditions.
On the other hand, there are some differences between skilled catchers and unskilled ones, for example - that the skilled ones start moving later then unskilled ones after the ball starts flying. So, something does change in their internal control systems, and perhaps it is only the gains of the visual 'ball catching' control systems, and perhaps it something else that we can try to explain.
4. Why do you think Bill included the section on Simulation and Modeling in this chapter?
AM:
Why it is in this chapter? I don't know. I could be a separate chapter from what I can tell. Modelling is a very important concept in PCT and other sciences.
5. What would you say is Bill's point in the last section of the chapter on Philosophy of Science? Why do you think he would include it?
AM:
The point is that what is missing from the study of life in sciences is the notion of control. He might have included this section to illustrate how fundamental the concept of control is to studying life, right down to the foundations of life acting according to physical laws.
6. Finally, consider the last sentence of the chapter: "Control, like digestion, is something everyone does but hardly anyone understands." Is Bill talking about these things -- control and digestion -- as theories or facts?
AM:
As facts. Humans digest and humans control. What is also important is that biological control is is hard to understand and we are just beginning to explore it.
Adam