A Feasible Genetic Optimization Strategy for Parametric Interval Type-2 Fuzzy Logic Systems

Arturo Téllez-Velázquez, Herón Molina-Lozano, Luis A. Villa-Vargas, Raúl Cruz-Barbosa, Esther Lugo-González, Ildar Z. Batyrshin, I. Rudas

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

This paper presents an optimization strategy for interval type-2 fuzzy systems by using the conjunction operation called the (p)-monotone sum of t-norms. A direct-current servomotor control system is implemented to test the performance of the type-1, interval type-2 and interval type-2 fuzzy systems with parametric operations, under several noisy conditions. To rate them, a multi-objective fitness function, based on the main transient parameters, is proposed to ensure the genetic algorithm to find the best squared feedback signal, when a white noise signal with different amplitudes is added to the reference. In addition, the optimization strategy includes the parametric conjunction suppression to analyze how a rule-associated parametric conjunction directly influences on system performance. Such rule suppression can be used to reduce the number of parametric conjunction operations required to obtain an additional performance improvement. Experimental results of the servomotor control system show that parametric conjunctions used in the interval type-2 fuzzy logic system provide additional advantages over its nonparametric counterpart.

Original languageEnglish
Pages (from-to)318-338
Number of pages21
JournalInternational Journal of Fuzzy Systems
Volume20
Issue number1
DOIs
Publication statusPublished - Jan 1 2018

Keywords

  • DC servomotor
  • Genetic algorithms
  • Monotone sum
  • Multi-objective transient fitness function
  • Parametric interval type-2 fuzzy logic system optimization

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'A Feasible Genetic Optimization Strategy for Parametric Interval Type-2 Fuzzy Logic Systems'. Together they form a unique fingerprint.

  • Cite this

    Téllez-Velázquez, A., Molina-Lozano, H., Villa-Vargas, L. A., Cruz-Barbosa, R., Lugo-González, E., Batyrshin, I. Z., & Rudas, I. (2018). A Feasible Genetic Optimization Strategy for Parametric Interval Type-2 Fuzzy Logic Systems. International Journal of Fuzzy Systems, 20(1), 318-338. https://doi.org/10.1007/s40815-017-0307-0