Optimization of interval type-2 fuzzy logic controller using quantum genetic algorithms

Shill, Pintu Chandra; Amin, Md. Faijul; Akhand, M. A. H.; Murase, Kazuyuki

doi:10.1109/fuzz-ieee.2012.6251207

Cited by 17 publications

(16 citation statements)

References 30 publications

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“…The truck backing problem is a well-known control problem that is generally used as a benchmark for the evaluation of new control algorithms (Wang et al, 2004;Shill et al, 2012). The path planning of the truck is determined by x, y, and ϕ, where x and y are the horizontal and vertical positions, respectively, and ϕ is the angle of the truck with respect to the horizontal axis.…”

Section: Simulations and Resultsmentioning

confidence: 99%

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Genetic-algorithm-based type reduction algorithm for interval type-2 fuzzy logic controllers

2015

Engineering Applications of Artificial Intelligence

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Section: Simulations and Resultsmentioning

confidence: 99%

“…Type reduction is performed to combine F i ðxÞ and the corresponding rule consequents. The center-of-sets type reduction (Karnik and Mendel, 2001;Shill et al, 2012) is used in this paper. Then, CðxÞ is all possible combinations of the centroids:…”

Section: Interval Type-2 Fuzzy Logic Controllersmentioning

confidence: 99%

Genetic-algorithm-based type reduction algorithm for interval type-2 fuzzy logic controllers

2015

Engineering Applications of Artificial Intelligence

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“…These methods are currently bio-inspired, which include GA, PSO and ACO [96]. There are also optimization methods that involve quantum computing, such as the Type-2 quantum fuzzy logic controller (T2QFLC) [97]. Similar to the T2 algorithms, there is no consensus as to which optimization method is best as of yet.…”

Section: Discussionmentioning

confidence: 99%

Review of Recent Type-2 Fuzzy Controller Applications

et al. 2016

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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 include robotic control, bandwidth control, industrial systems control, electrical control and aircraft control. The most promising applications are found in the robotics and automotive areas, where T2 FLCs have been demonstrated and proven to perform better than traditional controllers. With the development of enhanced algorithms, along with the advancement in both hardware and software, we shall witness increasing applications of these frontier controllers.

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“…Eq. (27) can be used if no algorithms are used and random questions are involved in combination with several process models and applications [21]- [35].…”

Section: Application To a Set Of Imprecisementioning

confidence: 99%

A general formulation of abduction algorithms

Pozna

Precup

2012

2012 IEEE 3rd International Conference on Cognitive Infocommunications (CogInfoCom)

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The paper offers a general formulation of abduction algorithms, referred to as minimum length solution algorithms, which are based on all observable states. The algorithms compute the necessary evidence to derive the correct hypothesis in minimum steps. A first version of algorithms is proposed such that to deal with situations when not all states are observable. The development of fuzzy inference systems is presented in order to apply the minimum length solution algorithms to sets of imprecise observations. I.INTRODUCTION Cognitive reasoning represents the particular case of reasoning based on incomplete information. It is accepted that reasoning means to process and infer the premise information into conclusions. Several forms of logic inference are used in this context; they include the deduction, the induction and the abduction. The deduction is characterized by setting the necessity of the consequence. Two conditions are needed in this context, the observation of the premise and the knowledge on the fact that the premise causes the consequences. The induction states a necessary relation between two observations, the premise and the consequence. This statement is supported by several observations which link together the premise and the consequences.The abduction assumes the causal relation between two events. The abduction is needed when the causes of an observation are unknown, and that is possible if a set of hypotheses is available. The quality of this assumption can be a subject to a certain strategy and the well acknowledged Occam's razor principle is suggested in this framework. A hypothesis is based on the assumption that a certain premise is related to a particular observation. Using the previous experience each hypothesis has a certain degree of truth named the plausibility. Usually, several hypotheses can be proposed for a particular observation. These hypotheses form the observation's set of possible explanations.The ignorance can be classified in terms of incompleteness, imprecision and uncertainty. The incompleteness is the subject of non monotonic logic, the imprecision is the subject of fuzzy logic, and the uncertainty is the subject of probability theory. The combination of imprecision and uncertainty becomes the subject of evidence theory [1] or of possibility theory [2].The induction process in the machine learning theory employs input-output correspondences that are known, and the query is to find the function (the law) according to this correspondences. Using these correspondences one can predict future outputs caused by the not yet

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Optimization of interval type-2 fuzzy logic controller using quantum genetic algorithms

Cited by 17 publications

References 30 publications

Genetic-algorithm-based type reduction algorithm for interval type-2 fuzzy logic controllers

Genetic-algorithm-based type reduction algorithm for interval type-2 fuzzy logic controllers

Review of Recent Type-2 Fuzzy Controller Applications

A general formulation of abduction algorithms

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