Abstract
An efficient general-purpose fuzzy logic inference engine for real-time commercial embedded control and signal processing applications is reported. The monolithically implemented engine is capable of processing up to 64 rules, with up to 16 fuzzy membership functions per rule. Novel VLSI implementation is achieved through consideration of alternative computational techniques for fuzzy rule processing. Specifically, an embedded digital neural network is employed to rapidly compute minima across rule membership functions, achieving a computation rate of greater than 20 million fuzzy logical inferences per second. Additional implementation efficiency is achieved through algorithmic methods of membership function construction which are logically consistent with the theory of fuzzy sets. A proprietary method for constructing membership function values based on only the linear distance between an input and the user-defined membership function center value provides a highly efficient mans for constructing membership functions.
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