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HIPI Controller of IPMSM Drive using ALM-FNN

ALM-FNN을 이용한 IPMSM 드라이브의 HIPI 제어기

  • 고재섭 (순천대학교 전기제어공학과) ;
  • 최정식 (순천대학교 전기제어공학과) ;
  • 정동화 (순천대학교 전기제어공학과)
  • Published : 2009.08.31

Abstract

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper proposes hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme, The validity of the proposed controller is verified by results at different dynamic operating conditions.

종래의 고정된 이득을 가진 PI 제어기는 지령속도, 부하변화 등과 같은 파라미터 변동에 대해서 매우 민감하다. IPMSM 드라이브의 정확한 속도제어는 비선형적인 전자기적 발생저항뿐만 아니라 회전자 속도와 권선저항사이의 비선형적 관계 때문에 복잡한 문제점이 있다. 따라서 광범위한 동작상태에서 최적 제어를 위해 PI 제어기의 이득값을 실시간으로 조절해야한다. 본 논문은 FNN과 ALM을 이용하여 IPMSM 드라이브의 HIPI 제어기를 제시한다. 제시된 제어기는 ANN을 이용하여 속도를 추정하고, 시스템 외란에 대해서 IPMSM 드라이브의 고성능 속도제어를 제시한다. PI 제어기의 이득값은 모든 동작상태에서 ALM-FNN에 의해 최적화 되어진다. 제시된 제어기는 다양한 동작상태에 대한 분석을 통해 타당성을 입증한다.

Keywords

References

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