[Attachment Removed] Feedforward Demo

CSGnet Archive CSG2014
1

[From Bruce Abbott (2014.01.31.1915 EST)]

The recent discussion of feedforward versus feedback control systems, together with Rick Marken’s prompting, led me to create a demonstration program that shows off the advantage of feedforward control. The program was modified from the TrackAnalyze demo that is included in the suite of programs that accompany LCS III, and works in exactly the same way with one small difference: There is now a pair of radio buttons that can be set for either feedback or feedforward control.

The default setting is feedback control, or in other words the usual PCT control system. I encourage you to try this mode first. After you have started the program, click on the “Collect Data” button to begin. A green horizontal line with a gap in its center will appear along with a red horizontal line. For feedback control the green line serves as the target; your job is to do your best to keep the red cursor centered in the gap between the lines of the green target. Using the mouse, move the mouse pointer into the area where the target is; when you do this, the mouse pointer disappears and your mouse movements now control the movements of the red cursor. Practice pursuing the target with the cursor until you feel ready to record some data.

You will notice a significant lag between your mouse movements and the cursor movements. This lag simulates a system with a sluggish response to control inputs. (Imagine the Titanic trying to turn away from the iceberg. The wheel was turn full to leeward as soon as the warning was given, but Titanic’s response to the helm was sluggish, and the rest is history.)

To record a data run, click on the “Start Recording” button at right (the mouse pointer will reappear when you move the mouse far enough to the right). You will then have four seconds to regain control of the cursor again and start pursuing the target. Do your best to keep the two aligned; after 60 seconds the run will end. Then click on the button at left labeled “Analyze Data.”

A window will pop up asking you for a filename to use for saving the data; you can keep the default if you wish or change the name to something descriptive such as “feedback.” The data from your run will be saved to disk and the Analysis window will appear.

In the Analysis window, two graphs are present. The top graph displays the target position, cursor position, and error (the difference between the two) for duration of the run. The bottom graph shows the results of the PCT model of the cursor (mouse) movements. You can adjust the model’s fit by changing the parameters of the model as shown above the graphs. Press the “auto fit” button to have the computer generate its “best fit.”

When you are ready to leave the analysis window, just click on the “End Analysis” button in the upper right corner.

For your second run, click on the radio button labeled “Feedforward.” The program will now run in feedforward mode. You should now think of the target as representing a disturbance that is varying over time. Use your mouse as before to keep the cursor aligned as closely as you can with the disturbance. Make your experimental run as before. When the run ends, click on the “Analyze Data” button and, when the window appears prompting you for a filename, save your data using a different name than before, e.g., “feedforward.” The Analysis window will appear and you can again view both the actual data from the run and the fit of the model, in this case, the feedforward model.

During the experimental run, by keeping the cursor aligned with the disturbance marker you were creating an output waveform that closely matches the disturbance waveform (how closely depends on how well you kept the cursor aligned with the disturbance). During the run, the disturbance values shown by the target position were being applied one second later to the controlled variable, which was not being displayed on the screen. At the same delay, the output waveform was being applied, inverted to the same controlled variable, thus cancelling the effect of the disturbance on the controlled variable (to the extent that you successfully tracked the disturbance). The analysis shows how well this feedforward model performed in dealing with the one second lag. You should notice a significant improvement compared to the feedback model.

A true Ashby-style feedforward model would simply sense the disturbance in advance of its impact on the controlled variable, invert the signal, and use that signal to develop a properly scaled output that closely mirrors the disturbance in its effect on the CV, but acting in the opposing direction. The result, theoretically, is errorless control, but physical limitations in the sensors and actuators mean that some error will be present. In this demo, I’ve used your own feedback control system (tracking the varying disturbance) to develop the opposing output, so there will be error in the output waveform as there always is with feedback control. Nevertheless, by tracking the disturbance BEFORE it has had a chance to affect the CV and then applying the inverted output in phase with the disturbance as it begins to affect the CV one second later, this system has vastly improved your ability to control the CV.

You can download the “Feedforward” demo from my website at https://sites.google.com/site/perceptualcontroldemos/home/other-demos . Put it in a convenient folder, unzip it, and click on the feedforward.exe file twice to run the demo. (You will need a PC for this demo.)

Enjoy!

Bruce

2

[From Rick Marken (2014.01.31.1730)]

Bruce Abbott (2014.01.31.1915 EST)--

BA: The recent discussion of feedforward versus feedback control systems,
together with Rick Marken's prompting, led me to create a demonstration
program that shows off the advantage of feedforward control.

RM: That's super Bruce! If that's what you think feedforward control
is then it's perfectly consistent with PCT, since the feedforward part
of this demo occurs in the environment connecting mouse to cursor. The
subject, of course, is just controlling the relationship between
cursor and target in both the feedback and feedforward conditions. The
subject does worse in the feedback condition because the connection
between mouse and cursor has that awful time lag, which it doesn't
have in the feedforward condition. So it's much easier to do the
feedback control in the feedforward condition than in the feedback
condition.

You give away the game in you description of what happens in the
feedforward condition:

BA: During the experimental run, by keeping the cursor aligned with the
disturbance marker you were creating an output waveform that closely matches
the disturbance waveform (how closely depends on how well you kept the
cursor aligned with the disturbance). During the run, the disturbance
values shown by the target position were being applied one second later to
the controlled variable, which was not being displayed on the screen.

RM: The "game" is that you are calling a variable that the subject
can't even perceive the "controlled variable". People (actually, all
control systems) can only control what they can perceive: behavior is
the control of perception, remember. So what you refer to as a
controlled variable is just a variable that _you_ want controlled; and
you can get it controlled by using the subject's mouse movements,
which nearly perfectly compensated for the disturbance during feedback
control, to compensate for that same disturbance when it is applied
one second later to the "controlled variable", as you say here:

BA: At the same delay, the output waveform was being applied, inverted to the
same controlled variable, thus cancelling the effect of the disturbance on the
controlled variable (to the extent that you successfully tracked the
disturbance).

RM: I think what this little exercise illustrates more than anything
about feedforward is the difference between the engineering and PCT
approach to understanding control. The engineer is interested in
control systems controlling things that they (the engineers) care
about; the PCTer is interested in what control systems care about
controlling for themselves. Thus, the engineer is interested in how
well the control system controls (in terms of dynamic dynamic
stability) variables that the engineer wants controlled; the PCTer is
interest in what the control system wants controlled and how it does
it. I think this is why you and Martin and I have never done any
research together even though we are all researchers ostensibly
interested in understanding control systems. We just see it (control)
from a different point of view, so we're tangled up in blue!

Best

Rick

···

The analysis shows how well this feedforward model performed
in dealing with the one second lag. You should notice a significant
improvement compared to the feedback model.

A true Ashby-style feedforward model would simply sense the disturbance in
advance of its impact on the controlled variable, invert the signal, and use
that signal to develop a properly scaled output that closely mirrors the
disturbance in its effect on the CV, but acting in the opposing direction.
The result, theoretically, is errorless control, but physical limitations in
the sensors and actuators mean that some error will be present. In this
demo, I've used your own feedback control system (tracking the varying
disturbance) to develop the opposing output, so there will be error in the
output waveform as there always is with feedback control. Nevertheless, by
tracking the disturbance BEFORE it has had a chance to affect the CV and
then applying the inverted output in phase with the disturbance as it begins
to affect the CV one second later, this system has vastly improved your
ability to control the CV.

You can download the "Feedforward" demo from my website at
https://sites.google.com/site/perceptualcontroldemos/home/other-demos . Put
it in a convenient folder, unzip it, and click on the feedforward.exe file
twice to run the demo. (You will need a PC for this demo.)

Enjoy!

Bruce

--
Richard S. Marken PhD
www.mindreadings.com

The only thing that will redeem mankind is cooperation.
                                                   -- Bertrand Russell

3

[Martin Taylor 2014.01.31.23.53]

Bruce, I'm afraid I don't see the point of this demo. What it looks

like to me is that in the “feedforward” phase you are tracking
normally with no lag, because the output and disturbance are both
being delayed equally. The fitted model may have a controlled
variable that is delayed, but so far as I understand it, the human
does not. I don’t see where feedforward or prediction comes into it.
Maybe I’m not looking at it the way you see it.
Am I missing something, that you and Rick both think the problem
ought to arise when there’s no environmental feedback delay and the
effects of both output and disturbance are equally delayed in
perception? That would be a most unusual situation in the real
world, where perception usually is much faster than the effect of
output on the environmental variable. In the computer-simulated
world, we often make the “cursor” respond instantaneously to the
mouse, but that’s not the usual case in everyday life.
Martin

··· 
        [From Bruce

Abbott (2014.01.31.1915 EST)]

        The recent

discussion of feedforward versus feedback control systems,
together with Rick Marken’s prompting, led me to create a
demonstration program that shows off the advantage of
feedforward control. The program was modified from the
TrackAnalyze demo that is included in the suite of programs
that accompany LCS III, and works in exactly the same way
with one small difference: There is now a pair of radio
buttons that can be set for either feedback or feedforward
control.

4

Hi folks, I think one problem here is that being able to track our perception of a disturbance doesn’t actually tell us how to apply the correct output signals to the correct muscles to counteract the disturbance. I might see an asteroid coming to earth but have no idea how to stop it. Even a simple control loop can’t do that either I don’t think, until it’s parameters of its various output pathways (relative lags, gains, etc) are reorganised. Surely?

Warren

··· 
        [From Bruce

Abbott (2014.01.31.1915 EST)]

        The recent

discussion of feedforward versus feedback control systems,
together with Rick Marken’s prompting, led me to create a
demonstration program that shows off the advantage of
feedforward control. The program was modified from the
TrackAnalyze demo that is included in the suite of programs
that accompany LCS III, and works in exactly the same way
with one small difference: There is now a pair of radio
buttons that can be set for either feedback or feedforward
control.

5

[philip 2014.2.1.9.10]

Could someone define the exact meaning of the word “perception”. Contrast this meaning with the meaning of the word “memory”. And then explain what a “perception of a cause” is, making a clear distinction between the cause being that of a disturbance and the cause being that of a physical phenomenon.
Also, could someone please explain to me the difference between errorless control and errorless communication.

Phil

···

On Saturday, February 1, 2014, Warren Mansell wmansell@gmail.com wrote:

Hi folks, in fact, in real life, isn’t it that we only get a perception of the potential cause of the disturbance in advance of the disturbance itself. This perception is therefore subjectively perceived, probably within a different sensory modality (e.g. Vision rather than touch), and not even necessarily accurate (the upcoming lorry turns out to have no load and so doesn’t buffet the car), and it is not the actual disturbance - this can only perceived at the exact time it occurs, not before. The asteroid might miss earth…

I really like having to think round these things but it all comes round to a feedback to me, but with some clever trick that does allow some ‘perceived correlational association’ between information in our environment that is predictive of a later disturbance and the feedback system that corrects that disturbance as soon as it arrives. That would be a new little tweak to PCT, much like Bill manages in his memory chapter of B:CP.

I wonder whether we can model that?

Any thoughts Bruce, Rick, Martin?

Warren

Sent from my iPhone

On 1 Feb 2014, at 15:40, Bruce Abbott bbabbott@FRONTIER.COM wrote:

[From Bruce Abbott (2014.02.01.1040 EST)]

[Martin Taylor 2014.01.31.23.53] –

[From Bruce Abbott (2014.01.31.1915 EST)]

The recent discussion of feedforward versus feedback control systems, together with Rick Marken’s prompting, led me to create a demonstration program that shows off the advantage of feedforward control. The program was modified from the TrackAnalyze demo that is included in the suite of programs that accompany LCS III, and works in exactly the same way with one small difference: There is now a pair of radio buttons that can be set for either feedback or feedforward control.

MT: Bruce, I’m afraid I don’t see the point of this demo. What it looks like to me is that in the “feedforward” phase you are tracking normally with no lag, because the output and disturbance are both being delayed equally. The fitted model may have a controlled variable that is delayed, but so far as I understand it, the human does not. I don’t see where feedforward or prediction comes into it. Maybe I’m not looking at it the way you see it.

MT: Am I missing something, that you and Rick both think the problem ought to arise when there’s no environmental feedback delay and the effects of both output and disturbance are equally delayed in perception? That would be a most unusual situation in the real world, where perception usually is much faster than the effect of output on the environmental variable. In the computer-simulated world, we often make the “cursor” respond instantaneously to the mouse, but that’s not the usual case in everyday life.

I hope the diagram below will clarify:

<image003.jpg>

In Ashby’s feedforward controller (top diagram), the potential disturbance to a variable, x, is sensed before it reaches x. A mechanism (left box) converts the disturbance waveform into an appropriately scaled action waveform. The disturbance impinges on x after some delay and the counteracting action is applied to x at the same time. The controlled variable is simply x plus any residual error.

This feedforward system will work even if there is essentially no delay, so long as the action can be applied approximately in phase with the disturbance (similar to the delays present in the output of a feedback control system relative to variations in the disturbance). For the demo, I used a 1 second delay to emphasize the advantage of having advance information about the disturbance when delays are present.

For the demo, I did not have a way to get inside the participant’s nervous system and create the function shown in the left box of the Ashby controller. So instead, I had the participant act as a negative feedback control system to keep the cursor tracking the target. It’s important to keep in mind that in this case the target is supposed to represent the disturbance that is being sensed by the participant in advance of its arrival at the variable x that is to be controlled. To the extent that the participant accurately follows the target, the participant’s cursor movements will provide output actions that can be subtracted from x just as in the Ashby feedforward controller. The primary variable to be controlled here is x; this is achieved by acting to control the cursor position relative to the disturbance. Controlling the latter is the only the means by which x is controlled. The negative feedback controller (left box) is here being treated as equivalent to the input-output device of the Ashby-style feedforward control system.

In retrospect, I should have made the variable x explicit in the demo, to make it clear that it is x that is the variable to be controlled; controlling the target-cursor relationship is just the means through which this control over x is achieved. I could have made x follow its own waveform, completely different from that of the disturbance, while the participant’s actions almost completely oppose the disturbance’s effect on x.

In the “feedback” mode provided by the demo, the actions produced by the control system are delayed to simulate a situation in which control is sluggish. By the time the participant’s actions begin to have an influence on the CV, the disturbance value has changed, so that the action is not properly opposing the disturbance. The feedforward controller, by sensing the state of the disturbance in advance of its effects on the CV, allows actions to be developed early enough to compensate for the delay in the effects of those actions on the CV, thus allowing for good control despite these delays.

Bruce

6

I am not sure about some of those but B:CP includes a glossary and the memory chapter has a clear definition, something like the storage of a past perceptual signal…

···

Sent from my iPhone

On 1 Feb 2014, at 17:07, PHILIP JERAIR YERANOSIAN pyeranos@UCLA.EDU wrote:

[philip 2014.2.1.9.10]

Could someone define the exact meaning of the word “perception”. Contrast this meaning with the meaning of the word “memory”. And then explain what a “perception of a cause” is, making a clear distinction between the cause being that of a disturbance and the cause being that of a physical phenomenon.
Also, could someone please explain to me the difference between errorless control and errorless communication.

Phil

On Saturday, February 1, 2014, Warren Mansell wmansell@gmail.com wrote:

Hi folks, in fact, in real life, isn’t it that we only get a perception of the potential cause of the disturbance in advance of the disturbance itself. This perception is therefore subjectively perceived, probably within a different sensory modality (e.g. Vision rather than touch), and not even necessarily accurate (the upcoming lorry turns out to have no load and so doesn’t buffet the car), and it is not the actual disturbance - this can only perceived at the exact time it occurs, not before. The asteroid might miss earth…

I really like having to think round these things but it all comes round to a feedback to me, but with some clever trick that does allow some ‘perceived correlational association’ between information in our environment that is predictive of a later disturbance and the feedback system that corrects that disturbance as soon as it arrives. That would be a new little tweak to PCT, much like Bill manages in his memory chapter of B:CP.

I wonder whether we can model that?

Any thoughts Bruce, Rick, Martin?

Warren

Sent from my iPhone

On 1 Feb 2014, at 15:40, Bruce Abbott bbabbott@FRONTIER.COM wrote:

[From Bruce Abbott (2014.02.01.1040 EST)]

[Martin Taylor 2014.01.31.23.53] –

[From Bruce Abbott (2014.01.31.1915 EST)]

The recent discussion of feedforward versus feedback control systems, together with Rick Marken’s prompting, led me to create a demonstration program that shows off the advantage of feedforward control. The program was modified from the TrackAnalyze demo that is included in the suite of programs that accompany LCS III, and works in exactly the same way with one small difference: There is now a pair of radio buttons that can be set for either feedback or feedforward control.

MT: Bruce, I’m afraid I don’t see the point of this demo. What it looks like to me is that in the “feedforward” phase you are tracking normally with no lag, because the output and disturbance are both being delayed equally. The fitted model may have a controlled variable that is delayed, but so far as I understand it, the human does not. I don’t see where feedforward or prediction comes into it. Maybe I’m not looking at it the way you see it.

MT: Am I missing something, that you and Rick both think the problem ought to arise when there’s no environmental feedback delay and the effects of both output and disturbance are equally delayed in perception? That would be a most unusual situation in the real world, where perception usually is much faster than the effect of output on the environmental variable. In the computer-simulated world, we often make the “cursor” respond instantaneously to the mouse, but that’s not the usual case in everyday life.

I hope the diagram below will clarify:

<image003.jpg>

In Ashby’s feedforward controller (top diagram), the potential disturbance to a variable, x, is sensed before it reaches x. A mechanism (left box) converts the disturbance waveform into an appropriately scaled action waveform. The disturbance impinges on x after some delay and the counteracting action is applied to x at the same time. The controlled variable is simply x plus any residual error.

This feedforward system will work even if there is essentially no delay, so long as the action can be applied approximately in phase with the disturbance (similar to the delays present in the output of a feedback control system relative to variations in the disturbance). For the demo, I used a 1 second delay to emphasize the advantage of having advance information about the disturbance when delays are present.

For the demo, I did not have a way to get inside the participant’s nervous system and create the function shown in the left box of the Ashby controller. So instead, I had the participant act as a negative feedback control system to keep the cursor tracking the target. It’s important to keep in mind that in this case the target is supposed to represent the disturbance that is being sensed by the participant in advance of its arrival at the variable x that is to be controlled. To the extent that the participant accurately follows the target, the participant’s cursor movements will provide output actions that can be subtracted from x just as in the Ashby feedforward controller. The primary variable to be controlled here is x; this is achieved by acting to control the cursor position relative to the disturbance. Controlling the latter is the only the means by which x is controlled. The negative feedback controller (left box) is here being treated as equivalent to the input-output device of the Ashby-style feedforward control system.

In retrospect, I should have made the variable x explicit in the demo, to make it clear that it is x that is the variable to be controlled; controlling the target-cursor relationship is just the means through which this control over x is achieved. I could have made x follow its own waveform, completely different from that of the disturbance, while the participant’s actions almost completely oppose the disturbance’s effect on x.

In the “feedback� mode provided by the demo, the actions produced by the control system are delayed to simulate a situation in which control is sluggish. By the time the participant’s actions begin to have an influence on the CV, the disturbance value has changed, so that the action is not properly opposing the disturbance. The feedforward controller, by sensing the state of the disturbance in advance of its effects on the CV, allows actions to be developed early enough to compensate for the delay in the effects of those actions on the CV, thus allowing for good control despite these delays.

Bruce

7

Rick, would you mind trying to answer my question above. I haven’t had any productive correspondence with you in a while.

Thanks

···

On Saturday, February 1, 2014, Richard Marken rsmarken@gmail.com wrote:

[From Rick Marken (2014.02.01.0945)]

On Sat, Feb 1, 2014 at 8:42 AM, Warren Mansell wmansell@gmail.com wrote:

WM: Hi folks, in fact, in real life, isn’t it that we only get a perception of

the potential cause of the disturbance in advance of the disturbance itself.

RM: Right. I think that’s what’s going on in conditioning, which does

look a lot like feedforward or anticipatory control. But as you can

see from Bill’s description of the PCT model of conditioning in the

2011 paper you have up at PCTweb this phenomenon can be explained

without any changes to the PCT model; it’s still just feedback control

of perception. In classical conditioning, for example, the PCT

explanation of the apparent anticipation involved is that this is

simply reorganization driven development of of a new perceptual

function with the CS now becoming a disturbance to the perception that

was previously only disturbed by the US. So the dog that only

salivated to food in the mouth (food being a disturbance to the

perception of swallowability of the bolus) comes to salivate to the

sight of food, which have now come to be be a disturbance to the

perception of swallowability due to reorganization. It’s the

perception of “swallowability” that has changed, such that the CS

(sight of food) is now as much of a disturbance to it as the US (food

in mouth) had been. It’s all control of perception!

This perception is therefore subjectively perceived, probably within a

different sensory modality (e.g. Vision rather than touch), and not even

necessarily accurate (the upcoming lorry turns out to have no load and so

doesn’t buffet the car), and it is not the actual disturbance - this can

only perceived at the exact time it occurs, not before. The asteroid might

miss earth…

I really like having to think round these things but it all comes round to a

feedback to me, but with some clever trick that does allow some 'perceived

correlational association’ between information in our environment that is

predictive of a later disturbance and the feedback system that corrects that

disturbance as soon as it arrives. That would be a new little tweak to PCT,

much like Bill manages in his memory chapter of B:CP.

I wonder whether we can model that?

Any thoughts Bruce, Rick, Martin?

Warren

Sent from my iPhone

On 1 Feb 2014, at 15:40, Bruce Abbott bbabbott@FRONTIER.COM wrote:

[From Bruce Abbott (2014.02.01.1040 EST)]

[Martin Taylor 2014.01.31.23.53] –

[From Bruce Abbott (2014.01.31.1915 EST)]

The recent discussion of feedforward versus feedback control systems,

together with Rick Marken’s prompting, led me to create a demonstration

program that shows off the advantage of feedforward control. The program

was modified from the TrackAnalyze demo that is included in the suite of

programs that accompany LCS III, and works in exactly the same way with one

small difference: There is now a pair of radio buttons that can be set for

either feedback or feedforward control.

MT: Bruce, I’m afraid I don’t see the point of this demo. What it looks like

to me is that in the “feedforward” phase you are tracking normally with no

lag, because the output and disturbance are both being delayed equally. The

fitted model may have a controlled variable that is delayed, but so far as I

understand it, the human does not. I don’t see where feedforward or

prediction comes into it. Maybe I’m not looking at it the way you see it.

MT: Am I missing something, that you and Rick both think the problem ought

to arise when there’s no environmental feedback delay and the effects of

both output and disturbance are equally delayed in perception? That would be

a most unusual situation in the real world, where perception usually is much

faster than the effect of output on the environmental variable. In the

computer-simulated world, we often make the “cursor” respond instantaneously

to the mouse, but that’s not the usual case in everyday life.

I hope the diagram below will clarify:

<image003.jpg>

In Ashby’s feedforward controller (top diagram), the potential disturbance

to a variable, x, is sensed before it reaches x. A mechanism (left box)

converts the disturbance waveform into an appropriately scaled action

waveform. The disturbance impinges on x after some delay and the

counteracting action is applied to x at the same time. The controlled

variable is simply x plus any residual error.

This feedforward system will work even if there is essentially no delay, so

long as the action can be applied approximately in phase with the

disturbance (similar to the delays present in the output of a feedback

control system relative to variations in the disturbance). For the demo, I

used a 1 second delay to emphasize the advantage of having advance

information about the disturbance when delays are present.

For the demo, I did not have a way to get inside the participant’s nervous

system and create the function shown in the left box of the Ashby

controller. So instead, I had the participant act as a negative feedback

control system to keep the cursor tracking the target. It’s important to

keep in mind that in this case the target is supposed to represent the

disturbance that is being sensed by the participant in advance of its

arrival at the variable x that is to be controlled. To the extent that the

participant accurately follows the target, the participant’s cursor

movements will provide output actions that can be subtracted from x just –

Richard S. Marken PhD

www.mindreadings.com

The only thing that will redeem mankind is cooperation.

                                               -- Bertrand Russell
8

[From Rick Marken (2014.02.01.1030)]

On Sat, Feb 1, 2014 at 10:00 AM, PHILIP JERAIR YERANOSIAN

PY: Rick, would you mind trying to answer my question above. I haven’t had any

productive correspondence with you in a while.

RM: Yes, sure. Sorry. too many balls in the air. I’m doing this in a rush but I hope it helps. I presume the questions to which you refer are these:

[philip 2014.2.1.9.10]
Could someone define the exact meaning of the word “perception”. Contrast this meaning with the meaning of the word “memory”. And then explain what a “perception of a cause” is, making a clear distinction between the cause being that of a disturbance and the cause being that of a physical phenomenon.

Also, could someone please explain to me the difference between errorless control and errorless communication.

RM These are excellent questions. The most important one is what is a “perception” in PCT. I think it’s formally defined as a neural signal in an afferent pathway. This perceptual signal is the output of a perceptual function, which is a neural net that transforms raw sensory input (physical input at the sensory receptors) into a signal that represents aspects of this physical input, such as patterns, motions, sequences, principles, etc. AI look at perceptions as being similar to the outputs of the “receptive fields” discovered by Hubel and Weisel. Basically test are sensory arrays that are inputs to neural networks that produce out puts in single neurons, the amount of output being proportional to the degress to which they state of the sensory array “matches” what the receptive field is designed to “detect”. A mathematical way of looking at it is like this:

p = f(s.1,s.2…s.n)

where the s.i are the values of the sensory inputs to the perceptual function (neural network), f() is the function carried out by the neural network on the sensory inputs and p is the perception.

Another way of think of it is like what happens when you deposit a check using the automatic check reader. The input to the reader is just an array of different brightnesses. The system that reads the check has some very snazzy software that are the perceptual functions that can tell what’s going in in that input; where the amounts are written, what the characters are, etc. These are perceptions of what is in the input sensory array.

Memories are replays of stored perceptions; that are basically perceptions of perceptions; no sensory input.

A perception of cause is a perception of a type of relationship between on perception and another, such as that between one’s and a glass of water. We can perceive the hand as being near the glass or clutching the glass or causing the glass to move towards the mouse.

In PCT, a disturbance is always a physical variable and it is one (or possibly many) causes of variation in a controlled variable.

As far as errorless control and communication, I think the only difference between them is that errorless control would be a situation where a variable is always kept exactly equal to a reference value; in errorless communication the output of the communication channel is always equal to the input.

Best

Rick

···

–
Richard S. Marken PhD
www.mindreadings.com

The only thing that will redeem mankind is cooperation.

                                               -- Bertrand Russell
9

[From Bruce Abbott (2014.02.01.1400 EST)]

[philip 2014.2.1.9.10]–

PY: Could someone define the exact meaning of the word “perception”. Contrast this meaning with the meaning of the word “memory”. And then explain what a “perception of a cause” is, making a clear distinction between the cause being that of a disturbance and the cause being that of a physical phenomenon.

Also, could someone please explain to me the difference between errorless control and errorless communication.

Phil

In psychology a distinction is made between the terms “sensation” and “perception.” Sensation is the raw sensory experience; perception is the reality that the brain constructs based on sensory experience, heuristic rules that are built into the brain systems that deal with the sense modality in question (e.g., vision), memories, and so on. It’s what you make of the pattern of sensations, the reality you construct from them.

Perceptual control theory uses the term “perception” differently. In PCT, a perception is an input quantity arising from sensory receptors and represented in the nervous system as a scalar value. In PCT, a perception is created in an input function and one need not have any conscious awareness of it. For example, there is a control system that regulates the level of blood sugar and “perceives” the level of glucose in the bloodstream via certain receptors. We do not have any conscious awareness of the level of blood sugar, but in PCT the signal representing that level is called a perceptual signal.

Bill Powers speculated on the existence of a hierarchy of control systems, each system receiving inputs from below (via their perceptual input functions) and, except for the systems at the lowest level, outputting reference values to control systems one level below. A higher-level system manipulates the references of certain control systems one level below it as the means by which it controls its own, higher-level perception. The hierarchy of control systems implies a hierarchy of perceptions (see B:CP for details).

Bill also speculated that the reference values communicated to lower-level systems by those above them might first be stored and then “read out” to the lower-level systems. The memories referred to in PCT are these stored values.

To perceive a cause is to have a sensory input that corresponds to a variable that is acting to affect the state of some other variable. For example, I might perceive the wind (cause) that is acting to deflect the paths of passing cars (effect).

You ask to make “a clear distinction between the cause being a that of a disturbance and the cause being that of a physical phenomenon.” The question is improper because it assumes that disturbances and physical phenomena are different, but in fact disturbances are physical phenomena. Normally we use the term “disturbance” to refer to a physical phenomenon that is acting on a controlled variable. The actions of the control system act to oppose this effect, so that the controlled variable remains nearly unaffected by the disturbance.

Error in a control system is a difference between the reference and the perception. Such an error can arise from many causes (e.g., the effect of a disturbance to the controlled variable, a change in reference value that the system has not had time to fully adjust to, sensor errors, random “noise”). In the discussion of feedforward, we have been talking only about error that arises when the effect of a disturbance on the controlled variable is not completely opposed by the system’s actions. Theoretically a feedforward system such as that identified by Ashby could produce actions that would completely compensate for any potential effect of a disturbance on the controlled variable. A feedback system cannot do this, even in theory, because its actions develop as a result of error developing between the reference and perception. There must be error, or the feedback system cannot act.

Bruce

10

[philip 2014.02.01.13:16]

So if there must be error for feedback control to act, then how does the concept of errorless control make any sense at all?

Also, what about my other question - the difference between errorless control and errorless communication.

···

On Saturday, February 1, 2014, Bruce Abbott bbabbott@frontier.com wrote:

[From Bruce Abbott (2014.02.01.1400 EST)]

[philip 2014.2.1.9.10] –

PY: Could someone define the exact meaning of the word “perception”. Contrast this meaning with the meaning of the word “memory”. And then explain what a “perception of a cause” is, making a clear distinction between the cause being that of a disturbance and the cause being that of a physical phenomenon.

Also, could someone please explain to me the difference between errorless control and errorless communication.

Phil

In psychology a distinction is made between the terms “sensation” and “perception.” Sensation is the raw sensory experience; perception is the reality that the brain constructs based on sensory experience, heuristic rules that are built into the brain systems that deal with the sense modality in question (e.g., vision), memories, and so on. It’s what you make of the pattern of sensations, the reality you construct from them.

Perceptual control theory uses the term “perception” differently. In PCT, a perception is an input quantity arising from sensory receptors and represented in the nervous system as a scalar value. In PCT, a perception is created in an input function and one need not have any conscious awareness of it. For example, there is a control system that regulates the level of blood sugar and “perceives” the level of glucose in the bloodstream via certain receptors. We do not have any conscious awareness of the level of blood sugar, but in PCT the signal representing that level is called a perceptual signal.

Bill Powers speculated on the existence of a hierarchy of control systems, each system receiving inputs from below (via their perceptual input functions) and, except for the systems at the lowest level, outputting reference values to control systems one level below. A higher-level system manipulates the references of certain control systems one level below it as the means by which it controls its own, higher-level perception. The hierarchy of control systems implies a hierarchy of perceptions (see B:CP for details).

Bill also speculated that the reference values communicated to lower-level systems by those above them might first be stored and then “read out” to the lower-level systems. The memories referred to in PCT are these stored values.

To perceive a cause is to have a sensory input that corresponds to a variable that is acting to affect the state of some other variable. For example, I might perceive the wind (cause) that is acting to deflect the paths of passing cars (effect).

You ask to make “a clear distinction between the cause being a that of a disturbance and the cause being that of a physical phenomenon.” The question is improper because it assumes that disturbances and physical phenomena are different, but in fact disturbances are physical phenomena. Normally we use the term “disturbance” to refer to a physical phenomenon that is acting on a controlled variable. The actions of the control system act to oppose this effect, so that the controlled variable remains nearly unaffected by the disturbance.

Error in a control system is a difference between the reference and the perception. Such an error can arise from many causes (e.g., the effect of a disturbance to the controlled variable, a change in reference value that the system has not had time to fully adjust to, sensor errors, random “noise”). In the discussion of feedforward, we have been talking only about error that arises when the effect of a disturbance on the controlled variable is not completely opposed by the system’s actions. Theoretically a feedforward system such as that identified by Ashby could produce actions that would completely compensate for any potential effect of a disturbance on the controlled variable. A feedback system cannot do this, even in theory, because its actions develop as a result of error developing between the reference and perception. There must be error, or the feedback system cannot act.

Bruce

11

[From Bruce Abbott (2014.02.01.1645 EST)]

[philip 2014.02.01.13:16] –

PY: So if there must be error for feedback control to act, then how does the concept of errorless control make any sense at all?

Also, what about my other question - the difference between errorless control and errorless communication.
BA: Errorless control is theoretically possible with feedforward control as Ashby demonstrated. It is not even theoretically possible with feedback control because, as I emphasized previously, the output of such a control system is driven by error. However, one can get very close to errorless control in the feedback system if one can make the loop gain high enough. In that case large outputs can be generated by very small errors. If only a small output is needed to offset the effect of a disturbance on the controlled variable, the error will be driven down to the point that only a correspondingly small output will be produced, and in a high-gain system this equates to a very small error.

BA: As for your second question, sorry, I didn’t quite finish answering it last time, after describing what errorless control is. As Rick Marken (2014.02.01.1030) indicated, communication is errorless if the signal received exactly matches the signal that was transmitted along the communication channel. In a feedback control system, control is errorless if the system’s perceptual signal exactly matches the reference signal. In a feedforward control system, control is errorless if the system’s output exactly counteracts the influence of the disturbance on the controlled variable.

Bruce