I remember it being a huge thing in the late 90s where it was being applied to even washing machines and microwaves.
It was a Japanese concept if I remember right.
Did it just taper off or is it incorporated into current designs and firmware so that it need not be mentioned or emphasized anymore ?
Nothing happened to it; here is the thread:
Thanks 
The concept is still around, it’s just that the term “fuzzy logic” as a a buzz word has fallen out of fashion. But its ideas show up, for instance, a lot in machine learning when classifier algorithms give a value between zero and one that reflects the algorithm’s credence that a particular object belongs into a particular class.
The primary instigator of Fuzzy Logic and a collection of related Fuzzy subjects was Prof. Lotfi Zadeh at U. C. Berkeley, going back into the mid-1960s.
Probably the Japanese made it into the buzz word it was back then. Thank you for the info on the Prof.
Fuzzy logic was a particular kind of continuous-valued logic, and IMO, not a very useful one.
It tried to develop continuous versions of standard Boolean operators. For instance, an AND might be A*B–that gives the same results as a Boolean AND in the case of 0 and 1, and intermediate outputs for intermediate inputs. An OR might be max(A, B).
The problem is that these are immensely restrictive. Boolean logic has a finite number of possible operators, and the standard ones cover all bases. But there are an infinite number of possible fuzzy operators, and which one is most useful depends on the application.
Continuous-valued control systems were common long before fuzzy logic. They were and continue to be useful, because they didn’t restrict themselves to a handful of operators chosen only by analogy with Boolean math. They include far more powerful tools like derivative and integral operators.
And there are modern neural nets, which have a simple non-linear operator at their core (not immensely different from the ones used in fuzzy logic), but with trained weighting factors, and used by the millions. They can model any reasonable function, but it would be impossible for a human to develop one by hand.
Fuzzy logic sits in an awkward middle ground between these two extremes. Too inflexible to be used directly; adding training could make them work, but then the Boolean analogy is pointless (you’re better off with some other operator that’s better suited for training).
From a mathematician’s point of view (at least this mathematician’s) fuzzy logic (or fuzzy set theory) is handicapped by the lack of the concept of fuzzy subset. I was once talking to a guy trying to do fuzzy topology and he told that whenever he seemed to be veering into an area where he needed to deal with fuzzy subsets, he dropped that inquiry.
That lacuna can be filled, but doing so puts into the branch of mathematics called topos theory and the fuzzy logicians were not interested in that. Once that is done all the boolean operations, including negation, become obvious.