• Title, Summary, Keyword: Takagi-Sugeno

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A Study on the Stability of Takagi-Sugeno Fuzzy Control System (어핀 Takagi-Sugeno 퍼지 제어 시스템의 안정도에 대한 연구)

  • Kim, Eun-Tai;Kim, Dong-Yon;Park, Hyun-Sik;Park Mig-Non
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.36C no.7
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    • pp.56-64
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    • 1999
  • In this paper, a novel approach to the stability analysis of the continuous affine Takagi-Sugeno fuzzy control systems is proposed. The suggested analysis method is easily implemented by the recently spotlighted convex optimization techniques called Linear Matrix Inequalities (LMI). First, it derives the stability condition under which the affine Takagi-Sugeno fuzzy system is stable in the large. Next, the derived condition is recast in the formulation of LMI and numerically addressed. Finally, the applicability of the suggested methodology is highlighted via computer simulations.

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Optimal Fuzzy Control of Nonlinear Systems Described by Takagi-Sugeno Fuzzy Model (Takagi-Sugeno 퍼지 모델로 표현된 비선형 시스템의 최적 퍼지 제어)

  • Park, Yon-Mook;Park, Joo-Young
    • Proceedings of the KIEE Conference
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    • pp.2853-2855
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    • 1999
  • 본 논문은 TS(Takagi-Sugeno) 퍼지 모델로 표현된 비선형 시스템의 최적 퍼지 제어에 관한 새로운 설계 방법론을 제시하며, 최적 TS 퍼지 제어기의 매개 변수들을 설정하는 문제가 선형 행렬 부등식 문제로 표현될 수 있음을 보인다.

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The Stability of Continuous Time Affine Takagi-Sugeno Fuzzy Control System (연속 시간 어핀 Takagi-Sugeno 퍼지 제어 시스템의 안정도)

  • 김은태;이희진;김동연
    • Proceedings of the IEEK Conference
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    • pp.1023-1026
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    • 1999
  • In recent years, many studies have been conducted on fuzzy control since it can surpass the conventional control in several respects. In this paper, a novel approach to the stability analysis of the continuous-time affine Takagi-Sugeno fuzzy control system is proposed. The suggested analysis method is easily implemented by the recently spotlighted convex optimization techniques called Linear Matrix Inequalities (LMI).

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Takagi-Sugeno Fuzzy Controller for Efficiency Optimization of Induction Motor with Model Uncertainties (Takagi-Sugeno 퍼지 제어기를 이용한 불확실성을 포함한 유도전동기의 효율 최적화)

  • Lee, Sun-Young;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • pp.1646_1647
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    • 2009
  • In this paper, Takagi-Sugeno(T-S) fuzzy controller and search method are developed for efficiency optimization of induction motors(IMs). The proposed control scheme consists of efficiency controller and adaptive backstepping controller. A search controller for which information of input of T-S fuzzy controller is included in efficiency controller that uses a direct vector controlled induction motor. A sliding mode observer is designed to estimate rotor flux and an adaptive backstepping controller is used to control of speed of IMs. Simulation results are presented to validate the proposed controller.

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Design of the Optimal Controller for Takagi-Sugeno Fuzzy Systems and Its Application to Spacecraft control (Takagi-Sugeno 퍼지시스템에 대한 최적 제어기 설계 및 우주 비행체의 자세 제어 응용)

  • Park, Yeon-Muk;Tak, Min-Je
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.7
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    • pp.589-596
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    • 2001
  • In this paper, a new design methodology for the optimal control of nonlinear systems described by the TS(Takagi-Sugeno) fuzzy model is proposed. First, a new theorem concerning the optimal stabilizing control of a general nonlinear dynamic system is proposed. Next, based on the proposed theorem and the inverse optimal approach, an optimal controller synthesis procedure for a TS fuzzy system is given, Also, it is shown that the optimal controller can be found by solving a linear matrix inequality problem. Finally, the proposed method is applied to the attitude control of a rigid spacecraft to demonstrate its validity.

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Robust Fuzzy Feedback Linearization Control Based on Takagi-Sugeno Fuzzy Models

  • Park, Chang-Woo;Park, Mignon
    • Transactions on Control, Automation and Systems Engineering
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    • v.4 no.4
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    • pp.356-362
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    • 2002
  • In this paper, well-known Takagi-Sugeno fuzzy model is used as the nonlinear plant model and uncertainty is assumed to be included in the model structure with known bounds. Based on the fuzzy models, a numerical robust stability analysis for the fuzzy feedback linearization regulator is presented using Linear Matrix Inequalities (LMI) Theory. For these structured uncertainty, the closed system can be cast into Lur'e system by simple transformation. From the LMI stability condition for Lur'e system, we can derive the robust stability condition for the fuzzy feedback linearization regulator based on Takagi-Sugeno fuzzy model. The effectiveness of the proposed analysis is illustrated by a simple example.

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.

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.

Design of Stabilizing Takagi-Sugeno Fuzzy Controllers - An LIM Approach (안정도를 보장하는 Takagi-Sugeno 퍼지 제어기의 설계 - 선형행렬부등식을 이용한 풀이 -)

  • 김진성;박주영;박대희
    • Journal of Korean Institute of Intelligent Systems
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    • v.8 no.5
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    • pp.51-60
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    • 1998
  • There have been several recent studies concerning the stability of fuzzy control system and the synthesis of stabilizing fuzzy controllers. This paper reports on a related study nf the TS (Takagi-Sugeno) fuzzy systems, and it is shown that the controller synthesis problems for the nonlinear systems described by the TS fuzzy model can be reduced to convex problems involving LMIs (linear matrix ineclualities). After classifying the TS fuzzy systems into three families based on how diverse their input matrices are, different controller synthesis procedure is given for each of these families. A numerical example is presented to illustrate the synthesis procedures developed in this paper.

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Development Of Active Vibration Isolation System Using Fuzzy Method (퍼지 방법을 이용한 능동 방진 시스템의 개발)

  • Yang, Xun;An, Chae-Hun;Jin, Kyoung-Bog;Rim, Kyung-Hwa
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • pp.731-736
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    • 2007
  • Vibration isolation equipments are mostly required in precise measurement and manufacturing system. Among all the vibration isolation system, air-spring is the most widely used equipment because of low resonant frequency and high damping ratio. In this study, Takagi-Sugeno fuzzy method is used to design an active vibration isolation system using air-spring, and compared the fuzzy method with passive control method and PID control method. Due to the non-linearity characteristics of air-spring, fuzzy controller was verified to be the most effective both in simulation and experiment.

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