• Title/Summary/Keyword: Fuzzy systems

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Controller Design for Continuous-Time Takagi-Sugeno Fuzzy Systems with Fuzzy Lyapunov Functions : LMI Approach

  • Kim, Ho-Jun;Joo, Young-Hoon;Park, Jin-Bae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.3
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    • pp.187-192
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    • 2012
  • This paper is concerned with stabilization problem of continuous-time Takagi-Sugeno fuzzy systems. To do this, the stabilization problem is investigated based on the new fuzzy Lyapunov functions (NFLFs). The NFLFs depend on not only the fuzzy weighting functions but also their first-time derivatives. The stabilization conditions are derived in terms of linear matrix inequalities (LMIs) which can be solved easily by the Matlab LMI Toolbox. Simulation examples are given to illustrate the effectiveness of this method.

Operations on Generalized Intuitionistic Fuzzy Soft Sets

  • Park, Jin-Han
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.3
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    • pp.184-189
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    • 2011
  • Generalized intuitionistic fuzzy soft set theory, proposed by Park et al. [Journal of Korean Institute of Intelligent Systems 21(3) (2011) 389-394], has been regarded as an effective mathematical tool to deal with uncertainties. In this paper, we prove that certain De Margan's law hold in generalized intuitionistic fuzzy soft set theory with respect to union and intersection operations on generalized intuitionistic fuzzy soft sets. We discuss the basic properties of operations on generalized intuitionistic fuzzy soft sets such as necessity and possibility. Moreover, we illustrate their interconnections between each other.

Notes on the compatibility between defuzzification and t-norm based fuzzy arithmetic operations

  • Hong, Dug-Hun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.2
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    • pp.231-236
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    • 2003
  • Recently, Oussalah 〔Fuzzy Sets and Systems 128(2002) 247-260〕 investigated some theoretical results about some invariance properties concerning the relationships between the defuzzification outcomes and the arithmetic of fuzzy numbers. But, in this note we introduce some explicit calculations of the resulting fuzzy set or possibility distribution when the matter is the determination of the defuzzified value pertaining to the result of some manipulation of fuzzy quantities under t-norm based fuzzy arithmetic operations.

Automatic Generation of Fuzzy Rules using the Fuzzy-Neural Networks

  • Ahn, Taechon;Oh, Sungkwun;Woo, Kwangbang
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1181-1186
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    • 1993
  • In the paper, a new design method of rule-based fuzzy modeling is proposed for model identification of nonlinear systems. The structure indentification is carried out, utilizing fuzzy c-means clustering. Fuzzy-neural networks composed back-propagation algorithm and linear fuzzy inference method, are used to identify parameters of the premise and consequence parts. To obtain optimal linguistic fuzzy implication rules, the learning rates and momentum coefficients are tuned automatically using a modified complex method.

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A Fuzzy Model of Systems using a Neuro-fuzzy Network

  • 정광손;박종국
    • Journal of the Korean Institute of Intelligent Systems
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    • v.7 no.5
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    • pp.21-27
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    • 1997
  • Neuro-fuzzy network that combined advantages of the neural network in learning and fuzzy system in inferencing can be used to establish a system model in the design of a controller. In this paper, we presented the neuro-fuzzy system that can be able to generated a linguistic fuzzy model which results in a similar input/output response to the original system. The network was used to model a system. We tested the performance ot the neuro-fuzzy network through computer simulations.

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On statistical testing for fuzzy hypotheses with fuzzy data (퍼지자료에 관한 퍼지가설의 통계적 검정)

  • 최규탁;이창은;강만기
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.255-258
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    • 2000
  • We prepose fuzzy statistical test of fuzzy hypotheses membership function with fuzzy number data. Finding the maximum grade of the meeting point for fuzzy hypotheses membership function and membership function of confidence interval. By the maximum grade, we obtain the results to acceptance or reject for the test of fuzzy hypotheses.

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Fuzzy (r, s)-preopen sets

  • Lee, Seung-On;Lee, Eun-Pyo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.2
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    • pp.136-139
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    • 2005
  • In this paper, we introduce the concepts of fuzzy (r,s)-preopen sets and fuzzy (r,s)-precontinuous mappings on intuitionistic fuzzy topological spaces in Sostak's sense and then we investigate some of their characteristic properties.