A VLSI Design and Implementation for a Real-Time Approximate Reasoning
  The role of inferencing with uncertainty is becoming more important in
rule-based expert systems (ES), since knowledge given by a human expert is
often uncertain or imprecise. We have succeeded in designing a VLSI chip which
can perform an entire inference process based on fuzzy logic. The design of the
VLSI fuzzy inference engine emphasizes simplicity, extensibility, and
efficiency (operational speed and layout area). It is fabricated in 2.5 um CMOS
technology. The inference engine consists of three major components; a rule set
memory, an inference processor, and a controller. In this implementation, a
rule set memory is realized by a read only memory (ROM). The controller
consists of two counters. In the inference processor, one data path is laid out
for each rule. The number of the inference rule can be increased adding more
data paths to the inference processor. All rules are executed in parallel, but
each rule is processed serially. The logical structure of fuzzy inference
proposed in the current paper maps nicely onto the VLSI structure. A two-phase
nonoverlapping clocking scheme is used. Timing tests indicate that the
inference engine can operate at approximately 20.8 MHz. This translates to an
execution speed of approximately 80,000 Fuzzy Logical Inferences Per Second
(FLIPS), and indicates that the inference engine is suitable for a demanding
real-time application. The potential applications include decision-making in
the area of command and control for intelligent robot systems, process control,
missile and aircraft guidance, and other high performance machines.
