Intuit before tuning: Type-1 and type-2 fuzzy logic controllers

Andriy Sarabakha, Changhong Fu, Erdal Kayacan*

*Corresponding author for this work

    Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

    Abstract

    Although a considerable amount of effort has been put in to show that fuzzy logic controllers have exceptional capabilities of dealing with uncertainty, there are still noteworthy concerns, e.g., the design of fuzzy logic controllers is an arduous task due to the lack of closed-form input–output relationships which is a limitation to interpretability of these controllers. The role of design parameters in fuzzy logic controllers, such as position, shape, and height of membership functions, is not straightforward. Motivated by the fact that the availability of an interpretable relationship from input to output will simplify the design procedure of fuzzy logic controllers, the main aims in this work are derive fuzzy mappings for both type-1 and interval type-2 fuzzy logic controllers, analyse them, and eventually benefit from such a nonlinear mapping to design fuzzy logic controllers. Thereafter, simulation and real-time experimental results support the presented theoretical findings.

    Original languageEnglish
    Article number105495
    JournalApplied Soft Computing Journal
    Volume81
    ISSN1568-4946
    DOIs
    Publication statusPublished - Aug 2019

    Keywords

    • Aerial robotics
    • Fuzzy mapping
    • Interval type-2 fuzzy logic controllers
    • Type-1 fuzzy logic controllers
    • Unmanned aerial vehicles

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