Keep in mind that fuzzy logic is not one technique: there are
fuzzy regressions, fuzzy clustering systems and so on. My
understanding is that fuzzy controllers are usually fuzzy rule
sets arranged in a matrix- really a look-up table with
interpolation. The advantage usually touted for fuzzy rule
systems is that they are easier to construct and easier to
understand. I suspect that this is more true for fuzzy rule
bases not confined to the giant matrix format.
"...and
2. what fuzzy logic controlers can do that a Neural Net can't?"
Assuming a sufficiently broad selection of each, theoretically
nothing.
-- Will Dwinnell Commercial Intelligence
############################################################################ This message was posted through the fuzzy mailing list. (1) To subscribe to this mailing list, send a message body of "SUB FUZZY-MAIL myFirstName mySurname" to listproc@dbai.tuwien.ac.at (2) To unsubscribe from this mailing list, send a message body of "UNSUB FUZZY-MAIL" or "UNSUB FUZZY-MAIL yoursubscription@email.address.com" to listproc@dbai.tuwien.ac.at (3) To reach the human who maintains the list, send mail to fuzzy-owner@dbai.tuwien.ac.at (4) WWW access and other information on Fuzzy Sets and Logic see http://www.dbai.tuwien.ac.at/ftp/mlowner/fuzzy-mail.info (5) WWW archive: http://www.dbai.tuwien.ac.at/marchives/fuzzy-mail/index.html