Home > technical > Normal, Slave, Almost Dead, Wimp, Unstable

Normal, Slave, Almost Dead, Wimp, Unstable


Mr. William T. Powers is the creator (discoverer?) of “Perceptual Control Theory” (PCT). In a nutshell, PCT asserts that “behavior controls perception“. His idea is the exact opposite of the stubborn, entrenched, behaviorist mindset which auto-assumes that “perception controls behavior“.

This (PCT) interpretation of behavior is not like any conventional one. Once understood, it seems to match the phenomena of behavior in an effortless way. Before the match can be seen, however, certain phenomena must be recognized. As is true for all theories, phenomena are shaped by theories as much as theories are shaped by phenomena. – Bill Powers

On the Living Control Systems III web page, you can download software that contains 13 interactive demos of PCT in action:

The other day, I spent several hours experimenting with the “LiveBlock” demo in an attempt to understand PCT more deeply. When the demo is launched, the majority of the window is occupied by a fundamental, building-block feedback control system:

When the “Auto-Disturbance” radio option in the lower left corner is clicked to “on“, a multi-signal time trace below the model springs to life:

As you can see, while operating under stable, steady-state circumstances, the system does what it was designed to do. It purposefully and continuously changes its “observable” output behavior such that its internal (and thus, externally unobservable) perceptual signal tracks its internal reference signal (also externally unobservable) pretty closely – in spite of being continuously disturbed by “something on the outside“. When the external disturbance is turned off, the real-time trace goes flat; as expected. The perceptual signal starts tracking the reference signal dead nutz on the money such that the difference between it and the reference is negligible:

The Sliders

Turning the disturbance signal “on/off” is not the only thing you can experiment with. When enabled via the control panel to the left of the model (not shown in the clip below),  six parameter sliders are  displayed:

So, let’s move some of those sliders to see how they affect the system’s operation.

The Slave

First, we’ll break the feedback loop by decreasing the “Feedback Gain” setting to zero:

Almost Dead

Next, let’s disable the input to the system by moving the “Input Gain” slider as far to the left as we can:

The Wimp

Next, let’s cripple the system’s output behavior by moving the “Output Gain” slider as far to the left as we can:

Let’s Go Unstable!

Finally, let’s first move the “Input Delay” slider to the right to decrease the response time and then subsequently move the “Output Time Constant” slider to the left to increase the reaction time:

So, what are you? Normal, a slave, almost dead, a wimp, or an unstable wacko (like BD00)?

I’ve always been pretty much a blue-collar type, by training and by preference. – Bill Powers

  1. W. Livingston
    August 2, 2012 at 11:07 am | #1

    A distinguishing characteristic of social system stability, as computed by control theory such as this, is that it is impossible even to attempt to defy those stability limits.

    • August 3, 2012 at 6:09 am | #2

      Interesting. But in individuals it is possible? Also, can individual instability be caused by too much gain?

      Thanks.

  2. William Livingston
    April 8, 2013 at 7:39 am | #3

    The comparison of Powers to Starkermann is essentially congruent. Starkermann was doing this dynamic simulation on university mainframes by 1962.

  1. August 9, 2012 at 5:39 am | #1
  2. August 17, 2012 at 6:03 am | #2
  3. March 18, 2013 at 5:49 am | #3

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