A NEW APPROACH OF MULTISTAGE FUZZY-LOGIC INFERENCE

In general multi-stage fuzzy logic inference, there are three kinds of linguistic variables: input, output, and intermediate variables. When intermediate variables are present in a set of fuzzy rules to form mu lti-stage fuzzy rules, the inferring time involved is understandably l engthened. To achieve fast reasoning of multi-sta fuzzy logic, the num ber of fuzzy set operations of input, output, and intermediate variabl es must be decreased as much as possible without information loss. For the intermediate variables, the fuzzy logic operations of overlapped fuzzy value pairs on several multi-stage fuzzy rules may be pre-comput ed at compiling time. Furthermore, if the pre-computations have been d one, the numbers of intersection and union scalar operations must also decrease in order to speed up reasoning at execution time. Moreover, whether fuzzy logic operations of multi-stage fuzzy rules are pre-comp uted or not, the types of fuzzy logic operators must be considered. Fa iling to do so may lead to information error. By using the Truck-Trail er Backer-Parking System, improvements over related methods are attain ed.