2016
DOI: 10.3390/a9020039
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Review of Recent Type-2 Fuzzy Controller Applications

Abstract: Type-2 fuzzy logic controllers (T2 FLC) can be viewed as an emerging class of intelligent controllers because of their abilities in handling uncertainties; in many cases, they have been shown to outperform their Type-1 counterparts. This paper presents a literature review on recent applications of T2 FLCs. To follow the developments in this field, we first review general T2 FLCs and the most well-known interval T2 FLS algorithms that have been used for control design. Certain applications of these controllers … Show more

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Cited by 83 publications
(41 citation statements)
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“…Since the popularity of fuzzy logic in 1965 [3], researchers have ventured it's application in soft-computing [4] such as control systems and supply chain [5]; some applied it as the driver of concepts and properties of ontologies in Semantic knowledge representation of uncertainty [6], [7], while others recently applied it in schools for evaluation [8], [9].…”
Section: Related Studiesmentioning
confidence: 99%
“…Since the popularity of fuzzy logic in 1965 [3], researchers have ventured it's application in soft-computing [4] such as control systems and supply chain [5]; some applied it as the driver of concepts and properties of ontologies in Semantic knowledge representation of uncertainty [6], [7], while others recently applied it in schools for evaluation [8], [9].…”
Section: Related Studiesmentioning
confidence: 99%
“…Based on Zadeh's theory, the T2-FLS is an extension of the T1-FLS. The membership function of a T2-FLS is a fuzzy set, unlike the T1-FLS which the membership function is a crisp number [22].…”
Section: Type-2 Fuzzy Logicmentioning
confidence: 99%
“…Their aim is to influence the control object in such a way so as to make that object operate in the way it is expected to. In the literature many types of control methods can be found including: adaptive control [37], fuzzy control [12,31], neuro-fuzzy control [29], fuzzy-integral-sliding [50], type-2 fuzzy control [48], internal model control [33], model predictive control [41], neural network control [20], nonlinear feedback linearization control [32], nonlinear optimal control [18], sliding mode control [24], etc. Although new types of controllers are still being sought for, controllers based on correction terms (proportional-integral-derivative-based controllers) still have an important place in control problems.…”
Section: Introductionmentioning
confidence: 99%