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Development of Self Tuning and Adaptive Fuzzy Controller to control of Induction Motor

유도전동기 드라이브의 제어를 위한 자기동조 및 적응 퍼지제어기 개발

  • 고재섭 (순천대학교 전기제어공학과) ;
  • 최정식 (순천대학교 대학원 전기제어공학과) ;
  • 정동화 (순천대학교 전기제어공학과)
  • Received : 2009.11.09
  • Accepted : 2010.01.22
  • Published : 2010.04.30

Abstract

The induction motor drive applied to field oriented control is widely used in industry applications. However, it is deceased performance and authenticity by saturation, temperature changing, disturbance and parameters changing because modeling of induction motor is nonlinear and complex. In order to control variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation, even under ideal field oriented conditions. This paper proposes self tuning PI controller based on fuzzy-neural network(FNN)-PI controller that is implemented using fuzzy control, neural network, and adaptive fuzzy controller(AFC). Also, this paper proposes estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FNN-PI, AFC and ANN controller. Also, this paper proposes the anlysis results to verify the effectiveness of controller.

벡터제어를 적용한 유도전동기 드라이브는 고성능 제어를 위하여 산업 적용분야에 광범위하게 사용되고 있다. 그러나 유도전동기의 모델은 비선형이고 복잡하기 때문에 포화, 온도변화, 외란 및 파라미터 변동등에 의해 성능 및 신뢰성이 저하된다. 이러한 가변속 드라이브를 제어하기 위하여 종래의 PI와 같은 제어기들이 일반적으로 사용되어졌다. 이러한 제어기들은 이상적인 벡터제어 상태에서도 광범위한 동작영역에서 양호한 성능을 나타내는데 한계를 가지고 있다. 본 논문은 퍼지제어, 신경회로망, 적응 퍼지제어로 구성된 FNN(Fuzzy-Neural Network)-PI 제어기 기반 자기동조 PI 제어기와 ANN을 이용한 속도추정을 제시한다. FNN-PI, AFC, ANN 제어기를 이용한 제어 알고리즘은 유도전동기 드라이브 시스템에 적용하여 그 결과를 분석하고 제어기의 효용성을 입증한다.

Keywords

References

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