• Title/Summary/Keyword: 자기구조화 퍼지 시스템

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Adaptive self-structuring fuzzy controller of wind energy conversion systems (풍력 발전 계통의 자기 구조화 적응 퍼지 제어기 설계)

  • Park, Jang-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.2
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    • pp.151-157
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    • 2013
  • This paper proposes an online adaptive fuzzy controller for a wind energy conversion system (WECS) that is intrinsically highly nonlinear plant. In real application, to obtain exact system parameters such as power coefficient, many measuring instruments and off-line implementations are required, which is very difficult to perform. This shortcoming can be avoided by introducing fuzzy system in the controller design in this paper. The proposed adaptive fuzzy control scheme using self-structuring algorithm requires no system parameters to meet control objectives. Even the structure of the fuzzy system is automatically grows on-line, which distinguishes our proposed algorithm over the previously proposed fuzzy control schemes. Combining derivative estimator for wind velocity, the whole closed-loop system is shown to be stable in the sense of Lyapunov.

State- and Output-feedback Adaptive Controller for Pure-feedback Nonlinear Systems using Self-structuring Fuzzy System (완전 궤환 비선형 계통에 대한 자기 구조화 퍼지 시스템을 이용한 상태변수 및 출력 궤환 적응 제어기)

  • Park, Jang-Hyun;Kim, Seong-Hwan;Jang, Young-Hak;Ryoo, Young-Jae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.9
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    • pp.1319-1329
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    • 2012
  • Globally stabilizing adaptive fuzzy state- and output-feedback controllers for the fully nonaffine pure-feedback nonlinear system are proposed in this paper. By reformulating the original pure-feedback system to a standard normal form with respect to newly defined state variables, the proposed controllers require no backstepping design procedures. Avoiding backstepping makes the controller structure and stability analysis to be considerably simplified. For the global stabilty of the clossed-loop system, the self-structuring fuzzy system whose memebership functions and fuzzy rules are automatically generated and tuned is adopted. The proposed controllers employ only one fuzzy logic system to approximate unknown nonlinear function, which highlights the simplicity of the proposed adaptive fuzzy controller. Moreover, the output-feedback controller of the considered system proposed in this paper have not been dealt with in any literature yet.