Re: [Phys-L] Teaching systems dynamic and feedback control

[John Denker <jsd@av8n.com>]

On 11/14/2014 08:21 AM, Roberto Carabajal wrote:
> Please, I need help to host a talk discussion about the problematic of -
> utilization of information technologies in the area of modeling and
> simulation for the teaching in exact sciences - (i.e. engineering). 

I don't want to be toooo nitpicky, but may I suggest the
term /natural sciences/ rather than "exact sciences"?

There are no "exact" sciences, except possibly for arithmetic.

Albert Einstein said: "Insofar as mathematics is exact, it does 
not apply to reality; and insofar as mathematics applies to 
reality, it is not exact."

> modeling and simulation [...]
> system dynamic [...]
> feedback control theory [...]

> The aim of the
> discussion is to know the overall educational situation,  and get
> recommendations to facilitate the integration of systems theory in
> engineering careers that are not specific to the topic.

Is it not already integrated?  I would have expected 
this topic to be already "built in" to every discipline 
from A to Z, literally from astronomy to zoology.  See 
list below.

So what is the problem we are trying to solve?  Are some
departments dropping the ball?  Are some students falling
through the cracks, not taking the courses where this sort
of thing is covered?  Is there any department that is /not/ 
using information technology for modeling?  Dynamical systems
have been a trendy subject for decades;  why is this suddenly 
a "problem"?

If the problem is various departments not talking to each
other, that is an endemic disease and an occupational hazard
in academia, nowhere near limited to the topic of dynamical
systems.  It takes more than an occasional panel discussion 
to keep this problem in check.

A: Astronomy:  The stability of rotating fluid bodies was
 studied in the 1880s: Lyapunov.

 The stability of planetary orbits against perturbation has 
 been a topic of discussion since the 1890s:
 Poincaré: _Les méthodes nouvelles de la mécanique céleste_

 And then there is stellar dynamics, including novas and
 supernovas.  Not to mention the origin and destiny of
 the universe as a whole.

A: Aviation:  The tradeoff between stability and control
 has been an issue since Day One.  (There were kites and
 gliders long before 1903.)  There are also issues with 
 control-system flutter.  Also pilot-induced oscillations.
 Perkins & Hage _Aircraft Stability and Control_

B: Biology: Apoptosis; homeostasis; tropism, et cetera.

C: Chemistry:  Basic notions of equilibrium, stability,
 reversibility, and spontaneity as applied to chemical
 reactions.

C: Cognitive science / bio-computation / computational
 learning / control theory:  The back-prop algorithm used 
 for training artificial neural networks can be traced 
 back to old-school control theory.
 Bryson & Ho: _Applied Optimal Control_
 Abu-Mostafa et al: _Learning from Data_

D: Dynamical systems theory:  A discipline unto itself.

E: Electronics:  Essentially every linear circuit has at
 least one feedback loop in it.  The EE curriculum has
 courses that go into this in gory detail, including
 year-long courses in circuit analysis and filter
 synthesis.

E/F: Economics and finance:  There are those who cultivate 
 instability in the financial markets, because they profit 
 from it.  This became kinda prominent in late 2008 ... and
 the issue has *not* gone away.

F: Fractals.

G: Genetics:  Control of gene expression.

I: Immunology:  A fantastically complex feedback system.

M: Mathematics:  A common thread in all of this.

M: Medicine: Homeostasis;  cardiac rhythm or lack thereof;
 et cetera.

M: Meteorology:  Butterfly effect.

N: Naval architecture.  Stability has been an issue for
 centuries.   http://en.wikipedia.org/wiki/Vasa_%28ship%29

N: Numerical analysis:  Lots of algorithms for numerical 
 integration suffer from marginal stability.  Ditto for 
 solving equations and finding roots.

P: Physics:  A common thread in almost all of this.  A
 two-piece compound pendulum suffices to exhibit chaotic
 motion.

P: Politics:  Instability -- due to delay followed by
 overreaction -- is par for the course.

Q: Queuing theory:  Applications to grocery stores, communication
 networks, transportation networks, et cetera.

R: Rocket science:  Pogo oscillations etc. etc. etc.

S: Systems engineering:  A discipline unto itself.

S: Sports industry:  Elaborate artifices to create the illusion
 of competition while preventing any one team from getting too
 strong.

T: Telecommunications:  Since the 1960s, modems have depended
 on adaptive filters.

T: Thermodynamics:  Entropy is at the heart of most definitions
 of stability, reversibility, and spontaneity.

Z: Zoology:  The Lotka-Volterra equation has been around
 since 1910 and has been applied to population dynamics
 since 1920.  It is famous as an example that is quantitative
 and simple enough to analyze, but capable of generating
 complex behavior.  It has been used as an example of
 deterministic chaos since the 1970s.

===========

This list could be expanded, but let's leave it for now.
You get the idea.