• Title/Summary/Keyword: ${\alpha}$-컷집합 분해

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Development of Fuzzy Inference Engine for Servo Control Using $\alpha$-level Set Decomposition ($\alpha$ -레벨집합 분해에 의한 서보제어용 퍼지 추론 연산회로의 개발)

  • 홍순일;이요섭
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.3
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    • pp.50-56
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    • 2001
  • As the fuzzy control is applied to servo system, the hardware implementation of the fuzzy information systems requires the high speed operations, short real time control and the small size systems. The aims of this study is to develop hardware of the fuzzy information systems to be apply to servo system. In this paper, we propose a calculation method of approximate reasoning for fuzzy control based on $\alpha$ -level set decomposition of fuzzy sets by quantize $\alpha$ -cuts. This method can be easily implemented with analog hardware. The influence of quantization Bevels of $\alpha$-cuts on output from fuzzy inference engine is investigated. It is concluded that 4 quantization levels give sufficient result for fuzzy control performance of dc servo system. The hardware implementation of proposed operation method and of the defuzzification by gravity center method which is directly converted to PWM actuating signal is also presented. It is verified useful with experiment for dc servo system.

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The development of fuzzy reasoning tool for the support design of servo system (서보 제어계 설계지원을 위한 퍼지추론 TOOL의 개발)

  • 노창주;홍순일
    • Journal of Advanced Marine Engineering and Technology
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    • v.19 no.4
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    • pp.72-78
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    • 1995
  • The diffusion of fuzzy logic techniques into real applications requires specific software supports which save development time and reduce the programming effort. But we has been lack of a tool devoted to support the design of fuzzy controllers. In this paper, on the basis of the general fuzzy set and .alpha.-cut set decomposition of fuzzy sets, a set of fuzzy reasoning tool(FRT) devoted to support the design of fuzzy dontroller for servo systems is developed. The major features of this tool are: 1) It supports users to analyze fuzzy ingerence status based on input deta and expected results by three-D graphic display. 2) It supports users to prepare input data and expected result. 3) It supports users to tuned scaling factor of membership functions, rules and fuzzy inference. The paper shows how the suggested design tools are suitable to give a consistent answer to the tuning of fuzzy control system. This FRT is expected to exert good performance and devoted to support which the design of fuzzy controller is illustrated in the servo systems.

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