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

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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.

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Acknowledgements

This work was partially supported by the following Mexican institutions: the Computing Research Center–National Polytechnic Institute (CIC–IPN), under project number SIP-IPN-20171344 and the National Council for Science and Technology (CONACyT), under the Catedra Program No. 1170. Any opinions, findings, conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the sponsoring agencies.

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Authors and Affiliations

  1. CONACyT – Technological University of the Mixteca Region, Huajuapan de León, 69000, Oaxaca, Mexico

    Arturo Téllez-Velázquez, Raúl Cruz-Barbosa & Esther Lugo-González

  2. Center for Computing Research – National Polytechnic Institute, Mexico City, 07738, Mexico

    Herón Molina-Lozano, Luis A. Villa-Vargas & Ildar Z. Batyrshin

  3. Obuda University, Budapest, Hungary

    Imre J. Rudas

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  1. Arturo Téllez-Velázquez
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  2. Herón Molina-Lozano
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Correspondence to Arturo Téllez-Velázquez.

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Téllez-Velázquez, A., Molina-Lozano, H., Villa-Vargas, L.A. et al. A Feasible Genetic Optimization Strategy for Parametric Interval Type-2 Fuzzy Logic Systems. Int. J. Fuzzy Syst. 20, 318–338 (2018). https://doi.org/10.1007/s40815-017-0307-0

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