• Title/Summary/Keyword: Type-2 Fuzzy Set

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A fuzzy-model-based controller for a helicopter system with 2 degree-of-freedom in motion (2 자유도 헬리콥터 시스템의 제어를 위한 퍼지 모델 기반 제어기)

  • Chang, Wook;Lee, Ho-Jae;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.1949-1951
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    • 2001
  • This paper deals with the control of a nonlinear experimental helicopter system by using the fuzzy-model-based control approach. The fuzzy model of the experimental helicopter system is constructed from the original nonlinear dynamic equations in the form of an affine Takagi-Sugeno (TS) fuzzy system. In order to design a feasible switching-type fuzzy-model-based controller, the TS fuzzy system is converted to a set of uncertain linear systems, which is used as a basic framework to synthesize the fuzzy-model-based controller.

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Design of pRBFNN Based on Interval Type-2 Fuzzy Set (Interval Type-2 퍼지 집합 기반의 pRBFNN 설계)

  • Kim, In-Jae;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.1871_1872
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    • 2009
  • 본 논문 에서는 Type-2 퍼지 논리 시스템을 설계하고, 불확실한 정보를 갖는 입력 데이터에 대하여 Type-1 퍼지 논리 시스템과 성능을 비교한다. Type-1 퍼지 논리 시스템은 외부 잡음에 민감한 단점을 가지고 있는 반면, Type-2 퍼지 논리 시스템은 불확실한 정보를 잘 표현 할 수 있다. 따라서 Type-2 퍼지 논리 시스템을 이용하여 이러한 단점을 극복하고자 2가지의 모델을 설계한다. 첫 번째 모델은 규칙의 전 후반부가 Type-1 퍼지 집합으로 구성된 Type-1 퍼지 논리 시스템을 설계 한다. 두 번째는 규칙 전 후반부에 Type-2 퍼지 집합으로 구성된 Type-2 퍼지 논리 시스템을 설계한다. 여기서 규칙 전반부의 입력 공간 분할 및 FOU(Footprint Of Uncertainty)형성에는 FCM(Fuzzy C_Means) clustering 방법을 사용하고, 입자 군집 최적화(Particle Swarm Optimization) 알고리즘을 사용하여 최적의 파라미터를 설계한다. 본 논문 에서는 또한 입력 데이터에 인위적으로 가하는 노이즈에 따른 각각 모델의 성능을 비교한다. 마지막으로 비선형 모델 평가에 주로 사용되는 NOx 데이터를 제안된 모델에 적용하고, 실험을 통하여 노이즈가 첨가되고, 불확실한 정보를 다루기에 Type-1 퍼지 논리 시스템 보다 Type-2 퍼지 논리 시스템이 효율적이라는 것을 보인다.

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Design of Radial Basis Function Neural Network Driven to TYPE-2 Fuzzy Inference and Its Optimization (TYPE-2 퍼지 추론 구동형 RBF 신경 회로망 설계 및 최적화)

  • Baek, Jin-Yeol;Kim, Woong-Ki;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.247-248
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    • 2008
  • 본 논문에서는 TYPE-2 퍼지 추론 기반의 RBF 뉴럴 네트워크(TYPE-2 Radial Basis Function Neural Network, T2RBFNN)를 설계하고 PSO(Particle Swarm Optimization) 알고리즘을 이용하여 모델의 파라미터를 동정한다. 제안된 모델의 은닉층은 TYPE-2 가우시안 활성 함수로 구성되며, 출력층은 Interval set 형태의 연결가중치를 갖는다. 여기에서 규칙 전반부 활성함수의 중심 선택은 C-means 클러스터링 알고리즘을 이용하고, 규칙 후반부 Interval set 형태의 연결가중치 결정에는 경사 하강법(Gradient descent method)을 이용한 오류 역전파 알고리즘을 사용하여 학습한다. 또한, 최적의 모델을 설계하기 위한 학습율 및 활성함수의 활성화 영역 결정에는 입자 군집 최적화(PSO; Particle Swarm Optimization) 알고리즘으로 동조한다. 마지막으로, 제안된 모델의 평가를 위하여 모의 데이터 집합(Synthetic dadaset)을 적용하고 근사화 및 일반화 능력에 대하여 토의한다.

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Performance Increase for a 2 kW Open Cathode Type Fuel Cell Using Temperature/Humidity Control (2 kW급 개방 캐소드형 연료전지 출력 향상을 위한 온습도 제어)

  • YUAN, WEIWEI;CHOI, MIHWA;YANG, SEUGRAN;KIM, YOUNG-BAE
    • Transactions of the Korean hydrogen and new energy society
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    • v.28 no.4
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    • pp.369-376
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    • 2017
  • Temperature and humidity regulations of an open-cathode PEM fuel cell with balance of plant (BOP) are developed in this study. The axial fan, a bubble humidifier, set of solenoid valves and a controller are used to perform temperature and humidity control simultaneously. A fuzzy controller is designed, and it shows its superiority in real-time controlling for strong non-linear dynamical fuel cell system. The axial fan speed is used for temperature control and solenoid valve on/off signal of the bubble humidifier is used for humidity control. The axial fan speed is controlled to keep the fuel cell temperature within the desired point. Meanwhile, the bubble humidifier is utilized to moisture hydrogen to manage the water content of membrane. The results show that the proposed fuzzy controller effectively increases the output power of 10% for a PEM fuel cell.

Household Types and Changes of Work-Family Time Allocation - Adapting Fuzzy-set Ideal Type Analysis - (일-가족 시간배분에 따른 가구유형과 변화 - 퍼지셋 이상형 분석의 적용 -)

  • Kim, Jin-Wook;Choi, Young-Jun
    • Korean Journal of Social Welfare
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    • v.64 no.2
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    • pp.31-54
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    • 2012
  • Along with increasing mothers' employment, work-family reconciliation has been recognised as a key policy agenda in contemporary welfare states. Although various policy instruments have been introduced and expanded in recent years, the problem of time allocation within couples still remains as a fundamental issue, which has been largely underresearched at a micro perspective. In this context, this study aims to identify dominant types of work-family time allocation within married couple, and to apply these types to the Korean case using the fuzzy-set ideal type analysis. Further, a series of multiple regression analyses will be implemented to find factors affecting each ideal type of work-family time allocation. The 1999 and 2009 Korea Time Use Survey datasets will be adopted for the analyses. Married couples are selected as samples only when men work 40 hours or more per week and they have at least one pre-school child. Empirical analyses cover three parts. First of all, four ideal types on work-family time allocation are classified by intersecting two core variables - the ratio of men's (paid) working and family (caring time plus domestic work) time to total working and family time. In this research, the four types will be labelled the traditional male breadwinner model (TM, high working and low family time), the dual burden model (DB, shared working but low family time), the family-friendly male breadwinner model (FM, high working but shared family time), and the adaptive partnership model (AP, shared working and shared family time). By comparing the composition of the four ideal types in 1999 and 2009, it will examine the trend of work-family time allocation in Korea. In addition, multiple regressions will be useful for investigating which characteristics contribute to the different degree of each fuzzy ideal score in the four models. Finally, policy implications and further research agenda will be discussed.

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PRODUCTION PLANNING IN FUZZY ENVIRONMENT

  • M, H-A
    • Journal of applied mathematics & informatics
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    • v.6 no.2
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    • pp.417-432
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    • 1999
  • This paper describes a fuzzy system designed to support production planning in an industrial unit producing cardboard boxes. In this industrial unit orders for n boxes of width w, length l, height h, made of q layers of type k paper for delivery in t units of time are produced. In the production of such orders apart from meeting the orders specifications it is usually tried to minimize the margin trim loss the number of machine setups and the holding cost of the finished orders. Considering the dynamism of production systems that are influenced by such factors as market demand fluctuations changes in commercial priorities raw material availability and pro-ducation capabilities we solve this multi-objective problem by fuzzy set theory.

The application of fuzzy spatial overlay method to the site selection using GSIS (GSIS를 이용한 입지선정에 있어 퍼지공간중첩기법의 적용에 관한 연구)

  • 임승현;조기성
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.17 no.2
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    • pp.177-187
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    • 1999
  • Up to date, in many application fields of GSIS, we usually have used vector-based spatial overlay or grid-based spatial algebra for extraction and analysis of spatial data. But, because these methods are based on traditional crisp set, concept which is used these methods. shows that many kinds of spatial data are partitioned with sharp boundary. That is not agree with spatial distribution pattern of data in the real world. Therefore, it has a error that a region or object is restricted within only one attribution (One-Entity-one-value). In this study, for improving previous methods that deal with spatial data based on crisp set, we are suggested to apply into spatial overlay process the concept of fuzzy set which is good for expressing the boundary vagueness or ambiguity of spatial data. two methods be given. First method is a fuzzy interval partition by fuzzy subsets in case of spatially continuous data, and second method is fuzzy boundary set applied on categorical data. with a case study to get a land suitability map for the development site selection of new town, we compared results between Boolean analysis method and fuzzy spatial overlay method. And as a result, we could find out that suitability map using fuzzy spatial overlay method provide more reasonable information about development site of new town, and is more adequate type in the aspect of presentation.

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Design on Fult Diagnosis System based on Dynamic Fuzzy Model (동적포지모델기반 고장진단 시스템의 설계)

  • 배상욱
    • Journal of the Korean Institute of Intelligent Systems
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    • v.10 no.2
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    • pp.94-102
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    • 2000
  • This paper presents a new FDI scheme based on dynamic fuzzy model(DFM) for the unknown nonlinear system, which can detect and isolate process faults continuously over all ranges of operating condition. The dynamic behavior of a nonlinear process is represented by a set of local linear models. The parameters of the DFM are identified by an on-line methods. The residual vector of the FDI system is consisted of the parameter deviations from nominal model and the set of grade of membership values indicating the operating condition of the nonlinear process. The detection and isolation of faults are performed via a neural network classifier that are learned the relationship between the residual vector and fault type. We apply the proposed FDI scheme to the FDI system design for a two-tank system and show the usefulness of the proposed scheme.

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Biosign Recognition based on the Soft Computing Techniques with application to a Rehab -type Robot

  • Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.29.2-29
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    • 2001
  • For the design of human-centered systems in which a human and machine such as a robot form a human-in system, human-friendly interaction/interface is essential. Human-friendly interaction is possible when the system is capable of recognizing human biosigns such as5 EMG Signal, hand gesture and facial expressions so the some humanintention and/or emotion can be inferred and is used as a proper feedback signal. In the talk, we report our experiences of applying the Soft computing techniques including Fuzzy, ANN, GA and rho rough set theory for efficiently recognizing various biosigns and for effective inference. More specifically, we first observe characteristics of various forms of biosigns and propose a new way of extracting feature set for such signals. Then we show a standardized procedure of getting an inferred intention or emotion from the signals. Finally, we present examples of application for our model of rehabilitation robot named.

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Labour Market Risk Shifts in 18 Post-industrial Economies: An Application of Fuzzy-set Ideal Type Approach (퍼지셋 이상형분석을 활용한 노동시장위험의 변화양상 분석: 후기산업사회 18개국 대상 비교연구)

  • Lee, Seung-yoon
    • 한국사회정책
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    • v.20 no.3
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    • pp.47-76
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    • 2013
  • The discussion of "new risks" in the field of social policy started to gain attention in the late 1990s and it is commonly argued that new risks are provoked by deindustrialization and/or globalization being more concentrated among the young, women and low skilled individuals. This study commences its inquiry with a conceptualization of labour market risk in an attempt to critically rethink the argument of new risk. A reevaluation of the concept is followed by an empirical investigation on the different types of risks and their changes by different degree. Eight-teen countries are selected in order to provide a comparative account to understand new risk. These are comparatively analyzed using the fuzzy-set ideal type approach to discover different types of social risks and to measure degrees of changes in relation to social risk. In sum, this paper aims to answer: what is new risk? and how do the characteristic of labour market risks differ in different post-industrial countries? The findings suggest that the types of risk are diverse and the speed or the directions of shift are also diverse.