• 제목/요약/키워드: fuzzy stability

검색결과 621건 처리시간 0.023초

STABILITYANALYSIS OF LINGUISTIC FUZZY MODEL SYSTEMS IN STATESPACE

  • Kim, Won C.;Woo
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.953-955
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    • 1993
  • In this paper we propose a new stability theorem and a robust stability condition for linguistic fuzzy model systems in state space. First we define a stability in linear sense. After representing the fuzzy model by a system with disturbances, A necessary and sufficient condition for the stability is derived. This condition is proved to be a sufficient condition of the fuzzy model. The Q in the Lyapunov equation is iteratively adjusted by an gradient-based algorithm to improve its stability test. Finally, stability robustness bounds of a system having modeling error is derived. An example is also included to show that the stability test is powerful.

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맘다니형 퍼지 시스템의 안정 해석 (A Stability Analysis of Mamdani Type Fuzzy Systems)

  • 이창훈;수게노미치오
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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    • pp.76-79
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    • 2001
  • This paper is concerned with a stability analysis of Madam Type fuzzy systems. It Introduces the canonical form of an unforced fuzzy system and its stability theorem suggested in the previous study. Then it gives new simplified stability conditions based on the Lyapunov function method. A common positive definite matrix in the stability conditions is searched by the LMI method.

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Robust Stability Analysis of Fuzzy Feedback Linearization Control Systems

  • Park, Chang-Woo;Lee, Chang-Hoon;Park, Mignon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제2권1호
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    • pp.78-82
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    • 2002
  • In this paper, we have studied a numerical stability analysis method for the robust fuzzy feedback linearization regulator using Takagi-Sugeno fuzzy model. To analyze the robust stability, we assume that uncertainty is included in the model structure with known bounds. For these structured uncertainty, the robust stability of the closed system is analyzed by applying Linear Matrix Inequalities theory following a transformation of the closed loop systems into Lur'e systems.

Stability Analysis of Fuzzy-Model-Based Controller by Piecewise Quadratic

  • Wook Chang;Joo, Young-Hoon;Park, Jin-Bae
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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    • pp.169-172
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    • 1999
  • In this paper, piecewise quadratic Lyapunov functions are used to analyze the stability of fuzzy-model-based controller. We represent the nonlinear system using a Takagi-Sugeno fuzzy model, which represent the given nonlinear system by fuzzy inference rules and local linear dynamic models. The proposed stability analysis technique is developed by dividing the whole fuzzy system into the smaller separate fuzry systems to reduce the conservatism. Some necessary and sufficient conditions for the proposed method are obtained. Finally, stability of the closed system with various kinds of controller for TS fuzzy model is checked through the proposed method.

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단일 입력 퍼지논리제어기의 안정성 분석 (Stability Analysis of Single-input Fuzzy Logic Controller)

  • 최병재
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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    • pp.47-51
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    • 2001
  • According as the controlled plants become more complex and large-scaled, the development of more intelligent control schemes is required in the control field. A fuzzy logic control (FLC) is one of proper schemes for this tendency. Recently, fuzzy control has been applied successfully to many industrial applications due to a number of advantages. But it still has some disadvantages. The conventional FLC has many tuning parameters: membership functions, scaling factors, and so forth. In order to improve this problem, a single-input fuzzy logic control (SFIC) which greatly simplifies the design process of the conventional FLC was proposed. Many research has also been proposed to develop the stability analysis of the FLC. In this paper we analyze the absolute stability of the SFLC. We first expand a nonlinear controlled plant into a Taylor series about a nominal operating point. And a fuzzy control system is transformed into a Lure system with nonlinearities. We also prove that the closed-loop system with the SFLC satisfies the sector condition globally.

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A novel smart criterion of grey-prediction control for practical applications

  • Z.Y. Chen;Ruei-yuan Wang;Yahui Meng;Timothy Chen
    • Smart Structures and Systems
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    • 제31권1호
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    • pp.69-78
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    • 2023
  • The purpose of this paper is to develop a scalable grey predictive controller with unavoidable random delays. Grey prediction is proposed to solve problems caused by incorrect parameter selection and to eliminate the effects of dynamic coupling between degrees of freedom (DOFs) in nonlinear systems. To address the stability problem, this study develops an improved gray-predictive adaptive fuzzy controller, which can not only solve the implementation problem by determining the stability of the system, but also apply the Linear Matrix Inequality (LMI) law to calculate Fuzzy change parameters. Fuzzy logic controllers manipulate robotic systems to improve their control performance. The stability is proved using Lyapunov stability theorem. In this article, the authors compare different controllers and the proposed predictive controller can significantly reduce the vibration of offshore platforms while keeping the required control force within an ideal small range. This paper presents a robust fuzzy control design that uses a model-based approach to overcome the effects of modeling errors. To guarantee the asymptotic stability of large nonlinear systems with multiple lags, the stability criterion is derived from the direct Lyapunov method. Based on this criterion and a distributed control system, a set of model-based fuzzy controllers is synthesized to stabilize large-scale nonlinear systems with multiple delays.

TSK퍼지 시스템의 안정도 해석 (Stability Analysis of TSK Fuzzy Systems)

  • 강근택;이원창
    • 한국지능시스템학회논문지
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    • 제8권4호
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    • pp.53-61
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    • 1998
  • 본 논문에서는 넓은 범위의 비선형 시스템들을 잘 표현할 수 있는 TSK(Takagai Sugeno Kang) 퍼지 시스템의 평형점의 지역 안정도를 해석하는 방법을 제시한다. TSK퍼지 모델은 TSK퍼지 규칙들로 구성되며, 각 규칙의 결론부는 상수항을 갖는 선형 입출력 방정식이다. TSK퍼지모델은 다수의평형점을 가질수 있으며, 각 평형점은 안정도에 있어서 역시 서로 단른 특징을 가질수 있다. 평형점의 지역 안정도는 평형점 부근에서 TSK퍼지 모델의 선형화로 얻어지는 자코비안 행렬의 교유치에 의해 결정된다. 본 논문에서는 연속시간 및 이산시간 시스템에 대한 안정도 해석을 위한 방법이 각각 제시된다.

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컴퓨터 연산을 통한 언어형 퍼지 제어 시스템의 새로운 안정도 해석: 1부 - 퍼지 시스템의 어핀 모델링 (A new computational approach to stability analysis of linguistic fuzzy control systems - Part l: Affine modeling of fuzzy system)

  • 김은태;박순형;박민용
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
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    • pp.169-172
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    • 2001
  • In recent years, many studies regarding the modeling of fuzzy system have been conducted. In this paper, a new computational approach to modeling of linguistic fuzzy system is proposed The fuzzy system is modeled as a combination of affine systems, The proposed method can be used in a rigorous stability analysis of fuzzy system including the linguistic fuzzy controller.

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어파인 퍼지 모델을 이용한 Chua 회로의 제어 (Control of Chua's Circuit using Affine Fuzzy Model)

  • 김은태
    • 전자공학회논문지SC
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    • 제40권4호
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    • pp.235-242
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    • 2003
  • 본 논문에서는 Chua회로의 카오스 현상을 안정화시키는 퍼지 제어기를 제안한다. 제안되는 퍼지 제어기는 두 가지 과정으로 설계되는데 우선 Chua 회로를 어파인 퍼지 모델로 표현하고 다음은 전체 폐루프의 안정도가 보장되도록 퍼지 제어기를 설계한다. 이를 위해 어파인 퍼지 시스템의 전역 점근 안정조건을 유도하고 이를 선형행렬부등식으로 표현하여 문제를 해결한다. 끝으로 컴퓨터 모의 실험을 통하여 타당성을 확인한다.