• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 추계학술대회 논문집
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• pp.359-362
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• 2009

Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed a novel efficiency optimization control of SynRM considering iron loss using multi adaptive fuzzy learning controller(AFLC). The optimal current ratio between torque current and exciting current is analytically derived to drive SynRM at maximum efficiency. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.94-96
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• 2007

This paper is proposed an efficiency optimization control algorithm for IPMSM which minimizes the copper and iron losses. The design of the speed controller based on adaptive fuzzy teaming control-fuzzy neural networks(AFLC-FNN) controller that is implemented using adaptive, fuzzy control and neural networks. The control performance of the AFLC-FNN controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.34-36
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• 2000

This paper proposes the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gain of input-output variables of fuzzy logic controller and weights of neural network using Tabu search. Neural network used to tune the output gain of FLC adaptively. We have weights of neural network learned using back propagation algorithm. We performed the nonlinear simulation on an single-machine infinite system to prove the efficiency of the proposed method. The proposed AFLC showed the better performance than PD controller in terms of the settling time and damping effect, for power system operation condition.

• 한국광학회지
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• 제13권2호
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• pp.162-165
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• 2002

본 논문에서는 반투과 반사판과 22.5$^{\circ}$의 in-plane tilt각을 가지며 λ/2로 설계된 반강유전성 액정 셀을 이용하여 새로운 형태의 반투과형 LCD모드의 구조를 제시하였다. 제안된 구조에서, 투과형 모드뿐만 아니라 광대역 λ/4 필름을 사용한 반사형 모드에서도 높은 밝기와 명암대비비를 구현해 낼 수 있었다.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2002년도 International Meeting on Information Display
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• pp.441-444
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• 2002

If an antiferroelectric liquid crystal (AFLC) cell is set between crossed polarizers for optical modulators or displays, it has low transmittance efficiency. This happens because AFLC materials have inherent tilt angles of typically $18^{\circ}{\sim}38^{\circ}$, not $45^{\circ}$. To improve the low transmittance efficiency, we propose a new optical configuration for antiferroelectric liquid crystal displays, which also improves color dispersion.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2000년도 제1회 학술대회 논문집
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• pp.93-94
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• 2000

In this work, we proposed a reflective antiferroelectric liquid crystal display (AFLCD) using a half-wave cell whose tilt angle is $22.5^{\circ}$. To check the validity of our design, we fabricated a reflective half-wave AFLC cell of which tilt angle is $24.9^{\circ}$, and measured viewing angle dependent reflectance and VIS reflection spectra. In the results, the half-wave AFLC cell in the reflective configuration exhibits high brightness, high contrast ratio of 20:1.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1007-1008
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• 2007

This paper is proposed an efficiency optimization control algorithm for IPMSM which minimizes the copper and iron losses. The design of the speed controller based on adaptive fuzzy learning control-fuzzy neural networks(AFLC-FNN) controller that is implemented using adaptive, fuzzy control and neural networks. The control performance of the AFLC-FNN controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm

• 한국광학회지
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• 제12권5호
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• pp.414-417
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• 2001

Experimentally, the aligned direction of AFLCs in electro-optic cells having both the substrates rubbed along the same direction is skewed by a few degrees from the rebbing direction. To explain why, we proposed "Torsional Rigid Body Model" and interpreted their skewing angle as the action of short pitch with the large shear stress. That is, the azimuthal an anchoring strength (about 35 dyn/cm) in the cell is much larger than the maximum shear stress (about 10$^{-6}$ dyn/cm) for the original pitch and so forbids the optic axis to skew. On the side hand, the strength is smaller than the maximum shear stress (about 42 dyn/cm) for short pitch and then allows the optic axis to skew.

• Journal of the Optical Society of Korea
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• 제5권2호
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• pp.39-42
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• 2001

A new method of switching mode in AFLC cell is proposed for faster switching time and higher contrast ratio. In this mode the ″dark″ state is obtained by applying negative full voltage while the ″bright″ state is achieved by applying positive full voltage to the cell. The switching time is reduced to 100 $mutextrm{s}$ for the cell whose switching time is 22 ms when operated in conventional mode. The contrast ratio is also improved vastly with this method. The possibility of achieving gray scale was shown in this mode of operation.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권5호
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• pp.249-256
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• 2000

This paper deals with the control of the lateral motion of a mobile vehicle. A mobile vehicle using in this experiment is able to adapt many unmanned automatic driving system, for example, like a automated product transporting system. This vehicle is consist of the two servomotors. One is used to accelerate this vehicle and the another is used to change this lateral direction. An adaptive fuzzy logic controller(AFLC) is designed and applied to a experimental mobile vehicle in order to achieve the control of the lateral direction. An adaptive fuzzy logic controller(AFLC) is designed and applied to a experimental mobile vehicle in order to achieve the control of the lateral motion of the vehicle. Therefore, the main aim of this paper is investigate the possibility of applying adaptive fuzzy control algorithms to a microprocessor-based servomotor controller which requires faster and more accurate response compared with many other industrial processes. Fuzzy control rules are derived by modelling an expert's driving actions. Experiments are performed using a mobile vehicle with sensing units, a microprocessor and a host computer.