Optimization of evolutionary strategies to achieve knowledge in faded temporal fuzzy logic controllers

摘要

In this document we carry out a comparative analysis of the reasoning strategies implemented in Fuzzy Logic Controllers (hereinafter FLCs) and Faded Temporal Fuzzy Logic Controllers (hereinafter FTFLCs). Starting from the problems associated to FLCs, we propose as a solution the use of FTFLCs. To improve the process of knowledge achievement in FTFLCs, it is introduced a mixed technique which combines the genetic learning in FLCs followed by the genetic learning in FTFLC.