A Parallel Inference Method of Fuzzy Rules using Transputers

Abstract

During the past decade, several specific hardware systems for fast fuzzy inference have been developed. However, most of them are dedicated to be executed sequentially, rule by rule, although they have parallel processing manners in operations of AND/OR computations. In this paper, we propose a parallel inference method of processing several fuzzy rules simultaneously by using T800 Transputer system, and analyze the worst case upper bound for internode message delays. The proposed control system has a relatively higher speedup, compared with the results of experiments in a single processor. This parallel inferencing fuzzy system can be used in a system requiring a rapid inference time in real-time system and/or one that has many inference variables in the condition part and the consequent part. Also, this system will be applied to build powerful architectures for control applications like robot control with time-critical sensor integration.