An advanced tuning methodology for fuzzy control: with application to a vacuum cleaner

A novel tuning algorithm is proposed as a design tool for the development of a fuzzy rule based controller. Given a set of action control rules in a fuzzy rule base structure, proposed algorithm computes the inconsistencies and redundancies in the overall rule set based on a newly proposed measure of equality of the individual fuzzy sets. An inconsistency and redundancy measure is computed for each rule in the rule base. Then the rules with high inconsistency and redundancy levels can be removed from the fuzzy rule base without affecting the overall performance of the controller. The algorithm is successfully tested experimentally for the control of a household vacuum cleaner. Experimental results demonstrate the effective use of the proposed algorithm.