Adaptive interval type-2 fuzzy logic controller for autonomous mobile robot

A Type-2 Fuzzy logic controller adapted with genetic algorithm, called type-2 genetic fuzzy logic controller (T2GFLC), is presented in this paper to handle uncertainty with dynamic optimal learning. Genetic algorithm is employed to simultaneous design of type-2 membership functions and rule sets for...

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Main Authors:	Shill, P.C., Akhand, M. A. H, Islam, Md. Saidul, Rahman, M.M. Hafizur
Format:	Article
Language:	English
Published:	Green University Press 2014
Subjects:	TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Online Access:	http://irep.iium.edu.my/39780/ http://irep.iium.edu.my/39780/ http://irep.iium.edu.my/39780/1/J16-02_Adaptive_FLC_for_Mobile_Robot_GreenUnv.pdf

id	iium-39780
recordtype	eprints
spelling	iium-397802018-06-19T06:59:18Z http://irep.iium.edu.my/39780/ Adaptive interval type-2 fuzzy logic controller for autonomous mobile robot Shill, P.C. Akhand, M. A. H Islam, Md. Saidul Rahman, M.M. Hafizur TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices A Type-2 Fuzzy logic controller adapted with genetic algorithm, called type-2 genetic fuzzy logic controller (T2GFLC), is presented in this paper to handle uncertainty with dynamic optimal learning. Genetic algorithm is employed to simultaneous design of type-2 membership functions and rule sets for type-2 fuzzy logic controllers. Traditional fuzzy logic controllers (FLCs), often termed as type-1 fuzzy logic systems using type-1 fuzzy sets, cannot handle large amount of uncertainties present in many real environments. Therefore, recently type-2 FLC has been proposed. The type-2 FLC can be considered as a collection of different embedded type-1 FLCs. However, the current design process of type-2 FLC is not automatic and relies on human experts. The purpose of our study is to make the design process automatic. Moreover, to reduce the computation time of T2GFLC an efficient type-reduction strategy for interval type-2 fuzzy set is also introduced. The evolved type-2 FLCs can deal with large amount of uncertainties and exhibit better performance for the mobile robot. Furthermore, it has outperformed their type-1 counterparts as well as the adaptive type-1 FLCs. Green University Press 2014-07 Article PeerReviewed application/pdf en http://irep.iium.edu.my/39780/1/J16-02_Adaptive_FLC_for_Mobile_Robot_GreenUnv.pdf Shill, P.C. and Akhand, M. A. H and Islam, Md. Saidul and Rahman, M.M. Hafizur (2014) Adaptive interval type-2 fuzzy logic controller for autonomous mobile robot. Green University Bangladesh (GUB) Journal of Science and Engineering, 1 (1). pp. 6-15. ISSN 2409-0476 http://green.edu.bd/academics/journal/45-gubjse/525-gubjse-volume-1-issue-1-july-2014.
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
spellingShingle	TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices Shill, P.C. Akhand, M. A. H Islam, Md. Saidul Rahman, M.M. Hafizur Adaptive interval type-2 fuzzy logic controller for autonomous mobile robot
description	A Type-2 Fuzzy logic controller adapted with genetic algorithm, called type-2 genetic fuzzy logic controller (T2GFLC), is presented in this paper to handle uncertainty with dynamic optimal learning. Genetic algorithm is employed to simultaneous design of type-2 membership functions and rule sets for type-2 fuzzy logic controllers. Traditional fuzzy logic controllers (FLCs), often termed as type-1 fuzzy logic systems using type-1 fuzzy sets, cannot handle large amount of uncertainties present in many real environments. Therefore, recently type-2 FLC has been proposed. The type-2 FLC can be considered as a collection of different embedded type-1 FLCs. However, the current design process of type-2 FLC is not automatic and relies on human experts. The purpose of our study is to make the design process automatic. Moreover, to reduce the computation time of T2GFLC an efficient type-reduction strategy for interval type-2 fuzzy set is also introduced. The evolved type-2 FLCs can deal with large amount of uncertainties and exhibit better performance for the mobile robot. Furthermore, it has outperformed their type-1 counterparts as well as the adaptive type-1 FLCs.
format	Article
author	Shill, P.C. Akhand, M. A. H Islam, Md. Saidul Rahman, M.M. Hafizur
author_facet	Shill, P.C. Akhand, M. A. H Islam, Md. Saidul Rahman, M.M. Hafizur
author_sort	Shill, P.C.
title	Adaptive interval type-2 fuzzy logic controller for autonomous mobile robot
title_short	Adaptive interval type-2 fuzzy logic controller for autonomous mobile robot
title_full	Adaptive interval type-2 fuzzy logic controller for autonomous mobile robot
title_fullStr	Adaptive interval type-2 fuzzy logic controller for autonomous mobile robot
title_full_unstemmed	Adaptive interval type-2 fuzzy logic controller for autonomous mobile robot
title_sort	adaptive interval type-2 fuzzy logic controller for autonomous mobile robot
publisher	Green University Press
publishDate	2014
url	http://irep.iium.edu.my/39780/ http://irep.iium.edu.my/39780/ http://irep.iium.edu.my/39780/1/J16-02_Adaptive_FLC_for_Mobile_Robot_GreenUnv.pdf
first_indexed	2023-09-18T20:57:06Z
last_indexed	2023-09-18T20:57:06Z
_version_	1777410377654468608

Adaptive interval type-2 fuzzy logic controller for autonomous mobile robot

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