Optimization of fuzzy logic controllers with rule base size reduction using genetic algorithms

@article{Shill2013OptimizationOF,
  title={Optimization of fuzzy logic controllers with rule base size reduction using genetic algorithms},
  author={Pintu Chandra Shill and M. A. H. Akhand and Md. Asaduzzaman and Kazuyuki Murase},
  journal={2013 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)},
  year={2013},
  pages={57-64}
}
In this paper, we present the automatic design methods with rule base size reduction for fuzzy logic controllers (FLCs). The adaptive schema is divided into two phases: the first phase is concerned with the adaptive learning method for optimizing the MFs parameters based on the binary coded genetic algorithms. The second phase is about the learning and reducing: automatically generate the fuzzy rules and at the same time apply the genetic reduction technique to determine the minimum number of… CONTINUE READING

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