• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 A
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• pp.216-218
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• 1995

In this article a neural network adaptive observer is proposed and applied to the case of induction motor control. The high performance vector control drives require exact knowledge of rotor flux. Because rotor time constant is needed to observe rotor flux, the accurate estimation of rotor time constant is important. For these problems, proposed observer which comprises neural network flux observer and neural network torque observer is trained to learn the flux dynamics and torque dynamics and subject to further on-line training by means of a backpropagation algorithem. Therefore it has been shown that the robust control of induction motor neglects the rotor time constant variations.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2013년도 전력전자학술대회 논문집
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• pp.269-270
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• 2013

This paper proposes the estimation algorithm to find the rotor time constant of induction motors, which is very important for induction motor drive system. This strategy is based on flux estimator theory. Proposed method has been demonstrated through simulation using MATLAB SIMULINK.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제52권2호
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• pp.87-92
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• 2003

This paper presents a flux estimator for the sensorless vector control of induction motors. The proposed method utilize the combination of the voltage model based on stator equivalent model and the current model based on rotor equivalent model, which enables stable estimation of rotor flux in high speed region and in low speed region. The dynamic performance of proposed method is verified through the experiment. The experimental results show that motors ran easily start even under 150[%] load condition and operate continuously below 0.5[Hz].

• 전기학회논문지
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• 제61권1호
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• pp.34-40
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• 2012

Flux linkage of phase windings or phase inductance is an important parameter in determining the behavior of a switched reluctance motor (SRM) [1-8]. Therefore, the accurate prediction of inductance at aligned and unaligned rotor positions makes a significant contribution to the design of an SRM and its analytical approach is not straightforward due to nonlinear flux distribution. Although several different approaches using a finite element analysis (FEA) or curve-fitting tool have been employed to compute phase inductance [2-5], they are not suitable for a simple design procedure because the FEA necessitates a large amount of time in both modeling and solving with complexity for every motor design, and the curve-fitting requires the data of flux linkage from either an experimental test or an FEA simulation. In this paper, phase inductance at aligned and unaligned rotor positions is estimated by means of numerical method and magnetic equivalent circuit as well, and the proposed approach is analytically verified in terms of the accuracy of estimated inductance compared to inductance computed by an FEA simulation.

• 대한전기학회논문지
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• 제38권11호
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• pp.877-887
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• 1989

In this paper, we attempt to achieve high dynamic performance by means of decoupled control of rotor speed and flux. Recently developed nonlinear feedback control theories are utilized. The rotor fluxes are estimated based on the rotor circuit equations. When the estimation error of the rotor flux tends to zero, the rotor speed and flux dynamic characteristics of the induction motor with our controller become linear. To minimize the deterioration of control performance, we use an identification algorithm for the rotor resistance. We analyze the dynamic behavior of the closed loop system with our controller. Both simulation and experimental results are included to demonstrate the practical significance of our result. In particular, our experimental results show that recently developed nonlinear feedback control techniques are of practical use in control of induction motors.

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.414-427
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• 2006

This paper presents an adaptive feedback linearization control scheme for induction motors with simultaneous variation of rotor and stator resistances. Two typical modeling techniques, rotor flux model and stator flux model, have been developed and successfully applied to the controller design and adaptive observer design, respectively. By using stator fluxes as states, over-parametrization in adaptive control can be prevented and control strategy can be developed without the need of nonlinear transformation. It also decrease the relative degree for the flux modulus by one, thereby, yielding, a simple control algorithm. However, when this method is used for flux observer, it cannot guarantee the convergence of flux. Similarly, the rotor flux model may be appropriate for observers, but it is not so for adaptive controllers. In addition, if these two existing methods are merged into overall adaptive control system, it brings about structural complexies. In this paper, we did not use these two modeling methods, and opted for the airgap flux model which takes on only the positive aspects of the existing rotor flux model and stator flux model and prevents structural complexity from occuring. Through theoretical analysis by using Lyapunov's direct method, simulations, and actual experiments, it is shown that stator and rotor resistances converge to their actual values, flux is well estimated, and torque and flux are controlled independently with the measurements of rotor speed, stator currents, and stator voltages. These results were achieved under the persistent excitation condition, which is shown to hold in the simulation.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제11B권2호
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• pp.51-58
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• 2001

This paper proposes a new strategy to estimate the rotor flux of an induction machine for the direct field oriented control. Electrical model of the induction machine presents the basic idea based on observer structure, which is composed of voltage model and current model. But the former has the defects in low speed range, the latter has the defects of sensitivity to machine parameters. In spite of these shortcomings, the closed loop flux observer based on two models has been prevalent estimation method for the direct field oriented control. In this paper, generalized analysis method named "observer characteristic function method"is proposed to analyze the kinds of the linear flux observers in unified form. With the observer characteristic function, the estimated rotor flux error involved in the classical methods can be easily clarified. Moreover, the novel rotor flux observer based on this analysis is also presented and the effectiveness of the observer has been verified by the simulation and experimental results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.306-309
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• 2003

This paper presents a speed estimation algorithm of Switched Reluctance Motor(SRM) using flux-linkage modeling. The basic algorithm of this scheme is based on the flux linkage characteristic according to the phase current and the rotor position. A sufficient simulation and experimental data was used for neural network training. Through measurement of the phase flux linkage and phase currents, the neural network is able to estimate the rotor position and speed. The simulation result shows some good results, and possibility of this algorithm.

• 전력전자학회논문지
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• 제10권2호
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• pp.155-161
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• 2005

본 논문에서는 MRAS 퍼지제어를 이용한 회전자 시정수 추정 기법을 제안한다. 회전자 자속을 추정하는 방법은 기준모델과 적응 회전자 모델을 이용한다 이 두 모델은 MRAS의 형태로 구성되며 두 모델의 오차를 영으로 근접하게 제어한다. 두 모델의 파라미터가 정확하면 동일한 결과를 얻는다. 그러나 회전자 시정수의 추정이 정확하게 이루어지지 않으면 두 회전자 자속의 추정은 서로 다른 각도를 가지게 된다. 두 모델의 오차와 오차 변화분을 입력으로 퍼지 제어기를 이용하여 회전자 시정수를 추정한다.

• 전력전자학회논문지
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• 제5권4호
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• pp.343-351
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• 2000

본 논문에서는 정렬과 비정렬된 회전자 위치들에서 자화곡선들을 기본으로 한 SRM의 회전자 워치펑가 알고리즘을 제안한다. 자화곡선은 측정된 상 전압과 상 전류로부터 계산되어지고, 계산된 데이타는 회전자 위치검출을 위한 자화곡선의 입력으로 사용되어진다. 자화곡선은 비션형 특성해석에 적합한 퍼지 알고리즘으로 구생되어졌다. 종래의 지삭기반 퍼지제어기를 이용한 자속관측기가 SRM의 센서리스 제어를 얻기 위해 제시되었다. 최적 각을 선정하기 위한 방식이 회전자 위치검출을 위해 제시되었다. 제안된 알고리즘의 강인성이 시뮬레이션과 실험결과의 비교를 통해 입증되었다.