• Title/Summary/Keyword: Affine fuzzy system

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Relaxed Stability Condition for Affine Fuzzy System Using Fuzzy Lyapunov Function (퍼지 리아푸노프 함수를 이용한 어파인 퍼지 시스템의 완화된 안정도 조건)

  • Kim, Dae-Young;Park, Jin-Bae;Joo, Young-Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.10
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    • pp.1508-1512
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    • 2012
  • This paper presents a relaxed stability condition for continuous-time affine fuzzy system using fuzzy Lyapunov function. In the previous studies, stability conditions for the affine fuzzy system based on quadratic Lyapunov function have a conservativeness. The stability condition is considered by using the fuzzy Lyapunov function, which has membership functions in the traditional Lyapunov function. Based on Lyapunov-stability theory, the stability condition for affine fuzzy system is derived and represented to linear matrix inequalities(LMIs). And slack matrix is added to stability condition for the relaxed stability condition. Finally, simulation example is given to illustrate the merits of the proposed method.

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

  • 김은태
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.40 no.4
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    • pp.235-242
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    • 2003
  • In this paper, a fuzzy controller is designed to suppress and stabilize the chaotic behavior of Chua's circuit. This controller is constructed by the following two phases. First, Chua's circuit is represented by an affine fuzzy model. Second, a fuzzy controller is designed so that the stability of the closed-loop system composed of the fuzzy controller and the affine fuzzy model of Chua's circuit is rigorously guaranteed. The stability condition of the affine fuzzy system is derived and is recast in the formulation of linear matrix inequalities. The guaranteed stability is global and asymptotic. Finally, the applicability of the suggested methodology is highlighted via computer simulations.

The Stabilization of an Affine TS Fuzzy System by using an ILMI method

  • Rhee, Bongjae;Won, Sangchul
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.35.2-35
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    • 2002
  • $\textbullet$ Introduction $\textbullet$ An affine fuzzy system $\textbullet$ The stabilization of an affine fuzzy system $\textbullet$ Iterative LMI algorithm for the stabilization $\textbullet$ A numerical example $\textbullet$ Conclusion

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

  • 김은태;박순형;박민용
    • Proceedings of the IEEK Conference
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    • 2001.06c
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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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Design of Controller for Affine Takagi-Sugeno Fuzzy System with Parametric Uncertainties via BMI

  • Lee, Sang-In;Joo, Young-Hoon;Park, Jin-Bae
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.658-662
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    • 2004
  • This paper develops a stability analysis and controller synthesis methodology for a continuous-time affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties. Affine T-S fuzzy system can be an advantage because it may be able to approximate nonlinear functions to high accuracy with fewer rules than the homogeneous T-S fuzzy systems with linear consequents only. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of bilinear matrix inequalities (BMIs). A simulation example is given to illustrate the application of the proposed method.

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Controller Design for Affine T-S Fuzzy System with Parametric Uncertainties (파라미터 불확실성을 갖는 어핀 T-S 퍼지 시스템의 제어기 설계)

  • Lee, Sang-In;Park, Jin-Bae;Joo, Young-Hoon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.04a
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    • pp.133-136
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    • 2004
  • This paper proposes a stability condition in affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties and then, introduces the design method of a fuzzy-model-based controller which guarantees the stability. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of linear matrix inequalities (LMIs).

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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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    • 1999.11a
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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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System simulation and synchronization for optimal evolutionary design of nonlinear controlled systems

  • Chen, C.Y.J.;Kuo, D.;Hsieh, Chia-Yen;Chen, Tim
    • Smart Structures and Systems
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    • v.26 no.6
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    • pp.797-807
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    • 2020
  • Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of concrete frame structures that adopt active controllers. Fuzzy theory is a relatively appropriate method but susceptible to human subjective experience to decrease the performance. This paper proposes a novel artificial intelligence based EBA (Evolved Bat Algorithm) controller with machine learning matched membership functions in the complex nonlinear system. The proposed affine transformed membership functions are adopted and stabilization and performance criterion of the closed-loop fuzzy systems are obtained through a new parametrized linear matrix inequality which is rearranged by machine learning affine matched membership functions. The trajectory of the closed-loop dithered system and that of the closed-loop fuzzy relaxed system can be made as close as desired. This enables us to get a rigorous prediction of stability of the closed-loop dithered system by establishing that of the closed-loop fuzzy relaxed system.

Controller Design for Discrete-Time Affine T-S Fuzzy System with Parametric Uncertainties (파라미터 불확실성을 갖는 이산시간 어핀 T-S 퍼지 시스템의 제어기 설계)

  • Lee, Sang-In;Park, Jin-Bae;Joo, Young-Hoon
    • Proceedings of the KIEE Conference
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    • 2004.07d
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    • pp.2516-2518
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    • 2004
  • This paper proposes a stability condition in discrete-time affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties and then, introduces the design method of a fuzzy-model-based controller which guarantees the stability. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of linear matrix inequalities (LMIs).

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Sliding Mode Controller Design Based On The Fuzzy Observer For Uncertain Nonlinear System (불확실한 비선형 시스템의 퍼지 관측기 기반의 슬라이딩 모드 제어기 설계)

  • 서호준;박장현;허성희;박귀태
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.284-284
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    • 2000
  • In adaptive fuzzy control systems. fuzzy systems are used to approximate the unknown plant nonlinearities. Until now. most of the papers in the field of controller design for nonlinear system using fuzzy systems considers the affine system with fixed grid-rule structure based on system state availability. This paper considers observer-based nonlinear controller and dynamic fuzzy rule structure. Adaptive laws for fuzzy parameters for state observer and fuzzy rule structure are established so that the whole system is stable in the sense of Lyapunov.

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