From: @   
      
   Luko wrote:   
      
   > Come back to the first question.   
   >   
   > Where and why not use fuzzy?   
   >   
   > I can use it in deterministic or stochastic cases, and then where do i   
   > can't?   
   >   
   > Luko   
   >   
   >   
      
   Hi:   
      
   In general, I do not use fuzzy logic whenever I have or I can derive   
   an equation or a set of equations expressing the relationship between   
   input and output variables. This does not mean that I actually implement   
   the system as an equation or a set of equations. In real-time embedded   
   systems where the requested response time is very difficult to achieve,   
   I prefer to replace the equation(s) with one or more look-up tables.   
      
   There is a caveat associated with what I wrote: the case in which small   
   errors in reading input variables result in major erroneous swings of   
   the output. In this case, normally, I first try to make sure I minimize   
   errors in reading input variables. Depending on the physical system,   
   there are various things I can do, i.e. time filtering, etc. In the case   
   in which this is difficult, I can still use a fuzzy system, as fuzzy   
   system can be designed to exhibit better error/fault tolerance. Maybe,   
   I should not say "better", but I should say that they are easier to   
   design with error/fault tolerance.   
      
   As a general issue, not related just to fuzzy systems, "When the only   
   tool you have is a hammer, everything looks like a nail".   
      
   I do not claim to have answered the question. There are other cases   
   when in which maybe I would not use fuzzy system. This is the most   
   obvious.   
      
   The best approach to problem solving is to have a wide toolbox, with   
   as many tools as possible, at least IMHO   
      
   Ciao   
      
   Bruno Di Stefano   
   fuzzy.logic.nuptek@sympatico.ca   
      
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