A brief comparison of fuzzy associative memory models for guiding autonomous problems

A brief comparison of fuzzy associative memory models for guiding autonomous problems

Authors

  • Guilherme Augusto de Lima Freitas Universidade Estadual de Londrina
  • Marcos Eduardo Valle Universidade Estadual de Londrina

DOI:

https://doi.org/10.5433/1679-0375.2011v32n2p151

Keywords:

Fuzzy set theory, fuzzy associative memory, inference engine, fuzzy controller

Abstract

Fuzzy associative memories (FAMs) are models inspired in the human brain ability to store and recall information. These models can be used for the storage of associations of fuzzy sets and, thus, they can be used as inference engines in fuzzy controllers. Several FAM models have been developed in the last years, but we are not aware of a work comparing the performance of novel FAMs in control. In this paper, we briefly investigate the performance of some FAMs in the automatic guidance problems of backing-up a truck (BT) and backing-up a truck and trailer (BTT). In particular, we note that the dual implicative fuzzy associative memories (co-IFAMs) constitute an interesting alternative to traditional models such as that of Kosko and Mamdani.

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Author Biographies

Guilherme Augusto de Lima Freitas, Universidade Estadual de Londrina

Discente de graduação em Engenharia Elétrica

Marcos Eduardo Valle, Universidade Estadual de Londrina

Docente do Departamento de Matemática.

Published

2011-12-15

How to Cite

Freitas, G. A. de L., & Valle, M. E. (2011). A brief comparison of fuzzy associative memory models for guiding autonomous problems. Semina: Ciências Exatas E Tecnológicas, 32(2), 151–166. https://doi.org/10.5433/1679-0375.2011v32n2p151

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Original Article
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