EXTRACTING CORE INFORMATION FROM INCONSISTENT FUZZY CONTROL RULES

In many cases, inconsistent fuzzy control rules can be obtained when t he information about the controlled plant is uncertain and/or the syst em is very complex. In most cases, inconsistent rules have been consid ered as ill-defined rules and, thus, not allowed to be in the same rul e base. One way to handle the situation is to try to extract core info rmation from the whole set containing the inconsistent rules. This app roach can be useful especially when it is difficult to separate consis tent rules from the set of inconsistent rules. In the paper, an infere nce scheme is presented to extract core information from such a rule b ase with inconsistent rules. The proposed inference scheme with the ai d of a statistical concept justifies application of all the rules with inconsistent rules in the same rule base for effective control of a c omplicated plant. A simulation study is performed for a truck-and-trai ler backer-upper control. The result shows that inconsistent rules can be effectively utilized if a proper inference method is adopted for t he extracted rules.