Abstract
A difficult problem in fuzzy logic is the development of a rule-base that is both complete and consistent. A Self-Learning Fuzzy Logic Control (SLFLC) methodology offers a possible solution. A robustness study is presented to illustrate the performance of the SLFLC by demonstrating its ability to generate a consistent set of rules to a predetermined criteria and by evaluating its transient performance over a variety of tests. The SLFLC has been applied to a laboratory liquid-level process. The on-line results presented show thai even with limited knowledge of the process, the self-learning procedure is able to yield a satisfactory performance with a degree of robustness and with high repeatability.
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