• Title/Summary/Keyword: Takagi-Sugeno 퍼지 추론

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Establishment and Application of Neuro-Fuzzy Real-Time Flood Forecasting Model by Linking Takagi-Sugeno Inference with Neural Network (I) : Selection of Optimal Input Data Combinations (Takagi-Sugeno 추론기법과 신경망을 연계한 뉴로-퍼지 홍수예측 모형의 구축 및 적용 (I) : 최적 입력자료 조합의 선정)

  • Choi, Seung-Yong;Kim, Byung-Hyun;Han, Kun-Yeun
    • Journal of Korea Water Resources Association
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    • v.44 no.7
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    • pp.523-536
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    • 2011
  • The objective of this study is to develop the data driven model for the flood forecasting that are improved the problems of the existing hydrological model for flood forecasting in medium and small streams. Neuro-Fuzzy flood forecasting model which linked the Takagi-Sugeno fuzzy inference theory with neural network, that can forecast flood only by using the rainfall and flood level and discharge data without using lots of physical data that are necessary in existing hydrological rainfall-runoff model is established. The accuracy of flood forecasting using this model is determined by temporal distribution and number of used rainfall and water level as input data. So first of all, the various combinations of input data were constructed by using rainfall and water level to select optimal input data combination for applying Neuro-Fuzzy flood forecasting model. The forecasting results of each combination are compared and optimal input data combination for real-time flood forecasting is determined.

Establishment and Application of Neuro-Fuzzy Flood Forecasting Model by Linking Takagi-Sugeno Inference with Neural Network (II) : Application and Verification (Takagi-Sugeno 추론기법과 신경망을 연계한 뉴로-퍼지 홍수예측 모형의 구축 및 적용 (II) : 실제 유역에 대한 적용 및 검증)

  • Choi, Seung-Yong;Han, Kun-Yeun
    • Journal of Korea Water Resources Association
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    • v.44 no.7
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    • pp.537-551
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    • 2011
  • Based on optimal input data combination selected in the earlier study, Neuro-Fuzzy flood forecasting model linked Takagi-Sugeno fuzzy inference theory with neural network in Wangsukcheon and Gabcheon is established. The established model was applied to Wangsukcheon and Gabcheon and water levels for lead time of 0.5 hr, 1 hr, 1.5 hr, 2.0 hr, 2.5 hr, 3.0 hr are forecasted. For the verification of the model, the comparisons between forecasting floods and observation data are presented. The forecasted results have shown good agreements with observed data. Additionally to evaluate quantitatively for applicability of the model, various statistical errors such as Root Mean Square Error are calculated. As a result of the flood forecasting can be simulated successfully without large errors in all statistical error. This study can greatly contribute to the construction of a high accuracy flood information system that secure lead time in medium and small streams.

Fuzzy Controller Design for Steam Temperature Control of Power Plant Superheater (화력발전소 과열기의 증기온도 제어를 위한 퍼지 제어기 설계)

  • 이돈구;이상혁;김주식;유정용
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.16 no.6
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    • pp.80-86
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    • 2002
  • In this paper, we present a method of fuzzy controller design for the power plant superheater in the form of bilinear system. For the steam temperature control, the input variables are constructed by the area of difference between the profiles estimated from bilinear observer and reference profiles, and the time rate of change. We estimate the control rules by T. Takagi and M. Sugeno's fuzzy model. The feasibilities of the suggested method are illustrated via the computer simulation results.

Automatic Generations and Representations of T-S Fuzzy Rule based on Neural Networks (신경망에 기초한 T-S 퍼지 규칙의 자동생성과 표현)

  • 황문선;오경환
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.310-316
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    • 1998
  • 본 논문에서는 기존의 퍼지 제어규칙에비해 좋은 성능을 갖는 T-S(Takagi-Sugeno)퍼지 모델을 자기조직화 지도와 역전파 신경망을 이용하여 표현하고 제어기 구현을 위한 규칙의 자동 생성 방법을 제안한다. 제안된 방법은 신경망에 기초하여 T-S 퍼지 제어 규칙을 포현하므로써 학습 기능을 이용하여 지식 획득을 용이하게 하고, 입력 변수간의 퍼지 관계에 기반 하여 추론이 이루어지므로 각 퍼지 변수에 대한 소속 함수의 정의 과정이 불필요하게 된다. 또한 제어기로 구현되었을 때 규칙의 수나 퍼지화 및 비퍼지화 등이 구성된 추론망을 통하여 자동으로 수행될 수 있다. 때문에 퍼지 시스템의 구현이 쉽게 이루어 질 수 있게 한다. 제안된 방법을 자동차 궤도 안정화 모의 실험에 적용해 봄으로써 추론망이 규칙을 생성하여 타당한 추론을 하게 됨을 확인한다.

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Local Separation Principle of Fuzzy Observer-Controller (퍼지 관측기-제어기의 국소적 독립 원리)

  • Lee, Ho-Jae;Park, Jin-Bae;Joo, Young-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.7
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    • pp.902-906
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    • 2004
  • A separation principle of the Takagj-Sugeno (T-S) fuzzy-model-based observer-control is investigated. When the premise variables are able to be measured or directly computed from the outputs of the T-S fuzzy system and the fuzzy inference rules for the plant, control, and observer share the premise parts, the T-S fuzzy-model-based observer and the T-S fuzzy-model-based control can be separately designed such that the global stabilizability is guaranteed by the fuzzy observer-based output-feedback control. In this case, the global separation principle is well established. On the other hand, when the premise variables are unmeasurable or cannot be computed from the outputs, they should also be estimated. We examine the separation principle of this case. If the decay rates of the T-S fuzzy-model-based control and observer are sufficiently fast, the global separation is assured. Otherwise we show that the separation principle holds locally.

A Study on the Design of Fuzzy Controller for a Turbojet Engine Model and its Performance Enhancement through Satisfactory Multiple Objectives (터보제트엔진의 퍼지제어기 설계 및 다목적함수 만족기법을 통한 제어성능 향상에 관한 연구)

  • Han,Dong-Ju
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.31 no.6
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    • pp.61-71
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    • 2003
  • In the study of control technique for a turbojet engine model, the Takagi-Sugeno fuzzy logic controller has been designed based on the model identification by the well designed PI controlled system through T-S neuro-fuzzy inference system. To enhance this designed controller, those procedures are proposed that certainty factors are adopted to each rule of objective groups which are classified by the fuzzy C-Means algorithm and the satisfaction degrees are matched to meet the objectives. This proposed technique shows its feasibility by upgrading performances of the previously well-designed T-S fuzzy controller.

A Study on Filament Winding Tension Control using a fuzzy-PID Algorithm (퍼지-PID 알고리즘을 이용한 필라멘트 와인딩 장력제어에 관한 연구)

  • 이승호;이용재;오재윤
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.3
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    • pp.30-37
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    • 2004
  • This thesis develops a fuzzy-PID control algorithm for control the filament winding tension. It is developed by applying classical PID control technique to a fuzzy logic controller. It is composed of a fuzzy-PI controller and a fuzzy-D controller. The fuzzy-PI controller uses error and integrated error as inputs, and the fuzzy-D controller uses derivative of error as input. The fuzzy-PI controller uses Takagi-Sugeno fuzzy inference system, and the fuzzy-D controller uses Mamdani fuzzy inference system. The fuzzy rule base for the fuzzy-PI controller is designed using 19 rules, and the fuzzy rule base for the fuzzy-D controller is designed using 5 rules. A test-bed is set-up for verifying the effectiveness of the developing control algorithm in control the filament winding tension. It is composed of a mandrel, a carriage, a force sensor, a driving roller, nip rollers, a creel, and a real-time control system. Nip rollers apply a vertical force to a filament, and the driving roller drives it. The real-time control system is developed by using MATLAB/xPC Target. First, experiments for showing the inherent problems of an open-loop control scheme in a filament winding are performed. Then, experiments for showing the robustness of the developing fuzzy-PID control algorithm are performed under various working conditions occurring in a filament winding such as mandrel rotating speed change, carriage traversing, spool radius change, and reference input change.