• 제목/요약/키워드: Induction Motor Drive, Fuzzy Control

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Fault Detection and Diagnosis System for a Three-Phase Inverter Using a DWT-Based Artificial Neural Network

  • Rohan, Ali;Kim, Sung Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제16권4호
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    • pp.238-245
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    • 2016
  • Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

GFPID 제어기에 의한 Pseudo-on-line Method를 이용한 유도전동기의 구동 (Drive of Induction Motors using Pseudo-on-line Method Based on Genetic Algorithms for Fuzzy-PID Controller(GFPID))

  • 권양원;윤양웅;강학수;안태천
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 D
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    • pp.2386-2388
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    • 2000
  • This paper proposes a novel method with pseudo-on-line scheme using look-up table based on the genetic algorithm. The technique is a pseudo-on-line method that optimally estimate the parameters of fuzzy PID(FPID) controller for systems with non-linearity using the genetic algorithm which does not use the gradient and finds the global optimum of an un-constraint optimization problem. The proposed controller(GFPID) is applied to speed control of 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed method is more excellent than conventional FPID and PID controllers.

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매트릭스 컨버터로 구동되는 유도전동기 구동장치를 위한 적응 퍼지 기법 기반의 슬라이딩 모드 제어기 (Adaptive Fuzzy based Sliding Mode Control for an Induction Motor Drive fed by a Matrix Converter)

  • 박기우;주성탁;박문수;이교범
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2008년도 추계학술대회 논문집
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    • pp.224-226
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    • 2008
  • 본 논문에서는 매트릭스 컨버터로 구동되는 유도전동기의 속도제어 성능을 향상시키기 위한 적응제어 기법을 제안한다. 유도 전동기는 비선형적 마찰력 등으로 인한 비선형적 특성을 가진다. 이러한 비선형적 특성으로 인해 야기되는 왜곡을 보상하고 속도제어 성능을 개선하기 위해 슬라이딩 모드 제어 기법을 적용한다. 슬라이딩 모드에서 발생하는 채터링 현상과 모델링되지 않은 유도 전동기의 불확실성에 의한 제어 성능 저하를 개선하기 위해, 불확실성 추정을 위한 퍼지 기반 불확실성 추정기를 적용한다. 시뮬레이션을 통해 제안한 제어기법의 타당성을 검증한다.

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