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Erdal Kayacan

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

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Intuit before tuning : Type-1 and type-2 fuzzy logic controllers. / Sarabakha, Andriy; Fu, Changhong; Kayacan, Erdal.

I: Applied Soft Computing Journal, Bind 81, 105495, 08.2019.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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Sarabakha, A, Fu, C & Kayacan, E 2019, 'Intuit before tuning: Type-1 and type-2 fuzzy logic controllers', Applied Soft Computing Journal, bind 81, 105495. https://doi.org/10.1016/j.asoc.2019.105495

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Sarabakha, Andriy ; Fu, Changhong ; Kayacan, Erdal. / Intuit before tuning : Type-1 and type-2 fuzzy logic controllers. I: Applied Soft Computing Journal. 2019 ; Bind 81.

Bibtex

@article{d410e800834845a682bed092ae5f144b,
title = "Intuit before tuning: Type-1 and type-2 fuzzy logic controllers",
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.",
keywords = "Aerial robotics, Fuzzy mapping, Interval type-2 fuzzy logic controllers, Type-1 fuzzy logic controllers, Unmanned aerial vehicles",
author = "Andriy Sarabakha and Changhong Fu and Erdal Kayacan",
year = "2019",
month = "8",
doi = "10.1016/j.asoc.2019.105495",
language = "English",
volume = "81",
journal = "Applied Soft Computing",
issn = "1568-4946",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - Intuit before tuning

T2 - Type-1 and type-2 fuzzy logic controllers

AU - Sarabakha, Andriy

AU - Fu, Changhong

AU - Kayacan, Erdal

PY - 2019/8

Y1 - 2019/8

N2 - 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.

AB - 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.

KW - Aerial robotics

KW - Fuzzy mapping

KW - Interval type-2 fuzzy logic controllers

KW - Type-1 fuzzy logic controllers

KW - Unmanned aerial vehicles

UR - http://www.scopus.com/inward/record.url?scp=85066011961&partnerID=8YFLogxK

U2 - 10.1016/j.asoc.2019.105495

DO - 10.1016/j.asoc.2019.105495

M3 - Journal article

VL - 81

JO - Applied Soft Computing

JF - Applied Soft Computing

SN - 1568-4946

M1 - 105495

ER -