At 00:20 30/10/96 EST, Dave Williams wrote:
>Like it or not, I think it is very difficult to design a control system without
>some using concepts from conventional theory-- take bandwidth for example.  If
>you have a system with a BW of 1000 hz.  (from measurements, calculations what
>have you) you better look for feedback transducers that have a response greater
>that 1000 hz. I am at a loss to understand how fuzzy would help a designer in
>choosing transducers for example. Or understanding frequency response in input
>signal conditioning.  I have been told that some fuzzy designers after
>completing the design run simulations to determine BW, etc.   But that seem
>backwards to me.  Maybe the fuzzy experts out there can answer these questions
>or point me in the right direction.

I haven't worked with fuzzy yet (but with "conventional" methods), but it
seems that a fuzzy design usually is based on a description of a _working_
solution in what they call lexical terms, i.e. like the example of the truck
moving backwards: you do not have to analyse the problem mathematically,
because you use an approximation to the (already proven to work) rules of a
(some) truck driver(s).

It seems obvious that you need some understanding (or a good understanding)
of the process involved, but not necessarily on a mathematically analytical
base. A good truck driver will bring that monster backwards in if possible
at all, and he wouldn't know to tell you the mathematics to be able to solve
it "classically". But he has a quite profund understanding of the process,
on another "plane", and maybe he can give you a set of those "lexical" rules.

It seems that fuzzy helps to use just these forms of understanding of a
process. With conventional methods it isn't easy at all to include the
intuitive knowledge of the people who often have worked successfully
controlling a process in a "manual" way, and you may end up not taking much
advantage of this knowledge. This I think is one of the major drawbacks to a
classical mathematical approach, which fuzzy may help to avoid.