Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10323825 | Fuzzy Sets and Systems | 2005 | 18 Pages |
Abstract
This paper introduces a recursive rule base adjustment to enhance the performance of fuzzy logic controllers. Here the fuzzy controller is constructed on the basis of a decision table (DT), relying on membership functions and fuzzy rules that incorporate heuristic knowledge and operator experience. If the controller performance is not satisfactory, it has previously been suggested that the rule base be altered by combined tuning of membership functions and controller scaling factors. The alternative approach proposed here entails alteration of the fuzzy rule base. The recursive rule base adjustment algorithm proposed in this paper has the benefit that it is computationally more efficient for the generation of a DT, and advantage for online realization. Simulation results are presented to support this thesis.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Pingkang Li, George W. Irwin, Uwe Kruger,