# Adaptive and Model Based Control

**URL:** <http://discourse.iapct.org/t/adaptive-and-model-based-control/864>\
**Category:** CSG1996\
**Created:** [July 16, 1996, 8:21pm UTC](http://discourse.iapct.org/t/adaptive-and-model-based-control/864 "1996-07-16T20:21:34Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![Richard\_Marken](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/r/9fc348/32.png) [@Richard\_Marken](http://discourse.iapct.org/u/Richard_Marken)\
**Post date:** [July 16, 1996, 8:21pm UTC](http://discourse.iapct.org/t/adaptive-and-model-based-control/864/1 "1996-07-16T20:21:34Z")

</div>

[From Rick Marken (960716.1330)]

Bill Leach (960715.1231)

> Model based control is anything but "minor" in engineering design.

I think what you are calling "model based control" is what I would call  
"adaptive control" (or reorganization in PCT).

> The first controllers that began "wearing the term 'model based' on their  
> shirtsleaves" were the adaptive controller...These controllers monitor their  
> own control error and change the parameters (and even the output functions  
> used) to reduce average and/or peak error based upon operating history.

I agree that this kind of adaptive control is important in engineered AND in  
living control systems; it's precisely what we call reorganization. Hans'  
model based controller does involve some adaptation; but the essense of model  
based "control" is output generation based on the model. This kind of control  
of output system will be successful (from the point of view of an observer)  
only after adaptation; that is, only after the appropriate "model" has been  
learned.

> We know from many sources that \_new\_ motor function tasks are controlled  
> poorly if at all when first attempted.

Yes. But we get better, not because we learn a model of the environment (as  
Hans' system does) but because we tune (adapt) the parameters and functions  
of our control organization (perceptual functions, output funcitons, gains,  
lags, etc) so that we control better. Hans' model based system learns the  
differential equations (environmental laws) that relate output to intended  
result. Then, when there is no perceeption of the result, the system can  
produce that result by simply specifying the appropriate outputs; control of  
output.

As Bill Powers noted in an earlier post, when perception is available, the  
model allows slightly improved control (relative to the plain vanilla PCT  
model) when the time constant of model based prediction is short; but then  
there is little gained from the model in terms of the ability to control when  
perception is lost. When the time constant of prediction is long, the model  
can produce the intended result without perceptual input for a much longer  
time than the PCT model; but in this case model based control no better  
than the PCT model when perception is present.

So the only thing to be gained from a model-based system like the one Hans is  
talking about is the ability to produce a particular result for a relatively  
long time (assuming no disturbance variations) when the perceptual  
representation of that result is lost. Then the question is, do people  
produce intended results for a long period of time when perception of the  
result is lost? We might but we have seen no evidence presented of it and if  
it does happen it is certainly "non-nominal".. Also, it's not clear that  
whatever ability there is to "control" without perception cannot be handled  
by the memory (and imagination) model Bill described in B:CP.

> As much as Hans seems to be argueing for "generated output" I get the  
> feeling that he does not really mean it the way that most of us usually take  
> him to mean.

I have looked at the code for and run Hans' model based controller. It is not  
just an adaptive controller, changing the parameters of a perceptual control  
system. It is an adaptive controller that is "adapting" a linear equation  
that is the system's "model" of the presumed environmental laws relating  
output to input. Once the model has learned the environmental equation you  
can switch off the perceptual input to the model and the system will generate  
outputs that produce the intended result. Hans' model based controller uses  
closed loop adaptation to learn a model that lets it act as an open loop  
"controller" (I put "controller" in quotes because the system cannot resist  
disturbances as long as it is running open loop).

> Adaptation and tuning of lower level control loops has been posited as a  
> form of learning and this process is undoubtedly also a model based control  
> operation.

Again, I think adaptive and model-based control are two different things. I  
think you are using "model based" control as a synonym for adaptive control;  
I think model-based control always must involve adaptive control (to learn  
the model) but not all adaptive control is "model based". Adaptive control is  
good old fashioned closed loop control where the controlled variable is a  
measure of the performance or another control system -- like error -- and  
the adaptive system controls this variable by manipulating paramters of the  
control system. Model based control, on the other hand, is aimed at output  
generation; the model may be built based on closed loop adaptive processes  
but the goal is to learn a model that will allow the production of intended  
results "in the blind".

Best

Rick

---

<div class="post-metadata">

**Author:** ![Bill\_Leach](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/b/59ef9b/32.png) [@Bill\_Leach](http://discourse.iapct.org/u/Bill_Leach)\
**Post date:** [July 17, 1996, 1:55am UTC](http://discourse.iapct.org/t/adaptive-and-model-based-control/864/2 "1996-07-17T01:55:47Z")

</div>

\<[Bill Leach 9960716.1754)]

> [From Rick Marken (960716.1330)]

> I think what you are calling "model based control" is what I would call  
> "adaptive control" (or reorganization in PCT).

Well we certainly are dealing with a matter of terms that can be difficult  
to "pin down". I suspect that the "line" between reoranization and model  
based control would be a fine one indeed.

One could easily consider reorganization to be "the model building  
mechanism" but I question the idea that all model changes are necessarily  
the result of random operations. For example, is it reorganization that  
"recognizes" a similarity between a new task and previous tasks? My idea  
there is that "it seems" that we sometimes employ existing task control  
loops to a new task by "connecting" them in some new and unique way while  
tuning the individual loop parameters. While it might be totally  
illusionary, it seems as though at least sometimes there is almost immediate  
success with the new task. Admittedly this is only conjecture.

> ... but the essense of model based "control" is output generation based on

the \>model. This kind of control of output system will be successful (from the

> point of view of an observer) only after adaptation; that is, only after

the \>appropriate "model" has been learned.

And this is a sticky part. In the sense that a model for getting to the  
store generates very high level reference signals I can sort of agree. When  
a task exists that involves "controlling" a perception that is a future  
perception that task is accomplished by setting references for the control  
current perceptions that, based upon one or more models should lead to the  
"control" of the future perception. This is most emphatically NOT S-R.

> Yes. But we get better, not because we learn a model of the environment (as  
> Hans' system does) but because we tune (adapt) the parameters and functions  
> of our control organization (perceptual functions, output funcitons, gains,  
> lags, etc) so that we control better. Hans' model based system learns the  
> differential equations (environmental laws) that relate output to intended  
> result.

The setting or selection of output functions would, in my opinion, BE an  
example of a model based control function. I don't see Hans' example program  
as having much to do with control from a PCT perspective. The use of math in  
the creation of a model of a model based control system is no more strange  
than our own use of math in the standard PCT models. It is the method of use  
of digital computers for emulation of analog operations.

> Then, when there is no perceeption of the result, the system can  
> produce that result by simply specifying the appropriate outputs; control of  
> output.

The idea that organisms construct models of the environment (aspects or  
characteristics of the environment), can and do use those models to create  
reference signals for lower level systems does not bother me a bit. I don't  
even have a problem with the idea that such systems do not perceive the  
perception that is to be controlled for over 95% of the time that the system  
is running as long as one accepts that there \_are\_ current perceptions, the  
current perceptions are related to the desired future perception by the  
model and that there are current perceptions that are being controlled in  
the usual PCT manner.

> ... Also, it's not clear that whatever ability there is to "control"

without \>perception cannot be handled by the memory (and imagination) model  
Bill \>described in B:CP.

The described handling would be model based control.

> ... that produce the intended result. Hans' model based controller uses  
> closed loop adaptation to learn a model that lets it act as an open loop  
> "controller" (I put "controller" in quotes because the system cannot resist  
> disturbances as long as it is running open loop).

And I agree. I don't consider Hans' model appropriate to model based control  
beyond the concepts of how the controller might create the model in the  
first place. It would take a great deal more thinking and experimentation  
than I have done to see how such a system might actually be able to work at  
the program level or above. I suspect that the implementation would be  
anything but trivial.

> Again, I think adaptive and model-based control are two different things. ...

Yes, sort of anyway. The problem in my mind with making the distinction that  
is always appropriate to engineered systems is that the adaptive system in  
living beings is created by the system itself and that process is a model  
based process.  
-bill  
b.leach@worldnet.att.org  
ars: kb7lx