• 충청수학회지
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• 제20권3호
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• pp.279-286
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• 2007

Using t-norm T and s-norm S, we introduce the notion of intuitionistic (T, S)-normed fuzzy subalgebra in BCK/BCI-algebra, and some related properties are investigated.

• Korean Journal of Mathematics
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• 제25권1호
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• pp.1-18
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• 2017

In this paper, we introduce the concepts of ([r, s], [t, u])-interval-valued intuitionistic fuzzy generalized preclosed sets and ([r, s], [t, u])-interval-valued intuitionistic fuzzy generalized preopen sets in the interval-valued intuitionistic smooth topological space and ([r, s], [t, u])-interval-valued intuitionistic fuzzy generalized pre-continuous mappings and then investigate some of their properties.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1862-1863
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• 2011

본 논문은 T-S Fuzzy Identification을 이용하여 PMSM를 모델링하고 T-S Fuzzy 제어로 PMSM을 제어하는 것 제안합니다. 시스템을 모델링을 위해서는 기존에는 파라미터를 알아야 가능했지만 시스템의 입출력 데이터를 가지고 T-S Fuzzy Identification을 하게 되면 쉽게 시스템을 모델링 할 수 있다. 논문에서는 T-S Fuzzy Identification을 통하여 모델링을 하고 T-S Fuzzy제어을 통해서 PMSM을 제어 할 수 있는 것을 보여주고 한다.

• Journal of information and communication convergence engineering
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• 제8권6호
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• pp.702-708
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• 2010

This paper proposes a novel linearization method for Takagi.sugeno (TS) fuzzy model. A T-S fuzzy controller consists of linear controllers based on local linear models and the local linear controllers cannot be designed independently because of overall stability conditions which are usually conservative. To use linear control theories easily for T-S fuzzy system, the linearization of T-S fuzzy model is required. However, The linearization of T-S fuzzy model is difficult to be achieved by using existing linearization methods because fuzzy rules and membership functions are included in T-S fuzzy models. So, a new linearization method is proposed for the T-S fuzzy system based on the idea of T-S fuzzy state transformation. For the T-S fuzzy system linearized with uncertainties, a robust optimal controller with the robustness of sliding model control(SMC) is designed.

• East Asian mathematical journal
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• 제22권1호
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• pp.93-109
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• 2006

The concept of intuitionistic fuzzy set was first introduced by Atanassov in 1986. In this paper, we define the intuitionistic(S,T)-fuzzy left h-ideals of a hemiring by using an s-norm S and a t-norm T and study their properties. In particular, some results of fuzzy left h-ideals in hemirings recently obtained by Jun, $\"{O}zt\"{u}rk$, Song, and others are extended and generalized to intuitionistic (S,T)-fuzzy ideals over hemirings.

• Korean Journal of Mathematics
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• 제9권2호
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• pp.149-156
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• 2001

We characterize some properties of $t$-fuzzy groups and $t$-fuzzy invariant groups and represent every subgroup S of a group X using the level set of $t$-fuzzy group constructed from S.

• 대한수학회보
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• 제39권4호
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• pp.653-663
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• 2002

We introduce and investigate the concepts of ($(T_i,T_j)$-fuzzy $\alpha-(r.s)$-semiopen $\alpha-(r.s)$-semiclosed) sets and fuzzy pairwise $\alpha-(r.s)$-semicontinuous mappings in smooth bitopological spaces.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제10권2호
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• pp.119-123
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• 2010

We introduce and investigate the concepts of ($T_i,T_j$)-fuzzy $\beta$-(r, s)-open sets, ($T_i,T_j$)-fuzzy $\beta$-(r, s)-closed sets and fuzzy pairwise $\beta$-(r, s)-continuous mappings in smooth bitopological spaces.

• 대한수학회논문집
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• 제14권2호
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• pp.393-403
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• 1999

Some fuzzy T\ulcorner-axioms are characterized in terms of the notion of fuzzy closure and the relationship between those fuzzy T\ulcorner-axioms are obtained. Also, finite fuzzy topological spaces satisfying one of those axioms are studied.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.419-422
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• 2005

In this note, the Takagi-Sugeno (T-S) fuzzy-model-based state estimator using standard Kalman filter theory is investigated. In that case, the dynamic system model is represented the T-S fuzzy model with the fuzzy state estimation. The steady state solutions can be found for proposed modeling method and dynamic system for maneuvering targets can be approximated as locally linear system. And then, modeled filter is corrected by the fuzzy gain which is a fuzzy system using the relation between the filter residual and its variation. This paper studies the T-S fuzzy model-based state estimator which the dynamic system can be approximated as linear system.