• 제어로봇시스템학회논문지
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• 제4권4호
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• pp.448-457
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• 1998

A neural network based control algorithm with fuzzy compensation is proposed for the automated adjustment in the production of electronic end-products. The process of adjustment is to tune the variable devices in order to examine the specified performances of the products ready prior to packing. Camcorder is considered as a target product. The required test and adjustment system is developed. The adjustment system consists of a NNC(neural network controller), a sub-NNC, and an auxiliary algorithm utilizing the fuzzy logic. The neural network is trained by means of errors between the outputs of the real system and the network, as well as on the errors between the changing rate of the outputs. Control algorithm is derived to speed up the learning dynamics and to avoid the local minima at higher energy level, and is able to converge to the global minimum at lower energy level. Many unexpected problems in the application of the real system are resolved by the auxiliary algorithms. As the adjustments of multiple items are related to each other, but the significant effect of performance by any specific item is not observed. The experimental result shows that the proposed method performs very effectively and are advantageous in simple architecture, extracting easily the training data without expertise, adapting to the unstable system that the input-output properties of each products are slightly different, with a wide application to other similar adjustment processes.

• 한국경영과학회지
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• 제17권3호
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• pp.67-78
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• 1992

MODM (multiobjective decision-making) problem is very complex system for the analyst. The problem is more complex if the goals of each of the objective functions are expressed imprecisely. It requires suitable MODM method to deal with imprecisions. Therefore, we present a new interactive fuzzy decision making method for solving multiobjective nonlinear programming problems by assuming that the decision maker (DM) has imprecise goals that assume fuzzy linguistic variable for each of the objective functions. The imprecise goals of the DM are quantified by eliciting corresponding membership functions through the interactive with the DM out of six membership functions. After determining membership functions, in order to generate the compromise or satisficing solution which is .lambda.-pareto optimal, .lambda.-max problem is solved. The higher degree of membership is chosen to satisfy imprecise goals of all objective functions by combining the membership functions. Then, the values are the compromise or satisficing solution. On the basis of the proposed method, and interactive computer programming is written to implement man-machine interactive procedures. Our programming is a revised version of sequential unconstrained minimization technique. Finally, a numerical example illustrates various aspects of the results developed in this paper.

• 한국자동차공학회논문집
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• 제8권3호
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• pp.85-97
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• 2000

In this paper, static and dynamic shift control stategies of CVT speed ratio are suggested. For the static shift control, in order to operate engine on the optimal operating region, a fuzzy control logic is used. In the fuzzy logic, S- factor that is defined as a degree of sportiness is introduced. Simulation results show that the static shift control strategy based on the fuzzy logic selects the optimal operating point automatically between the economy and the sporty mode corresponding to the driver's desire and the driving condition. For the dynamic shift control strategy, a shift speed map is suggested which determines the shift sped as fast or slow based on Δi, the difference between the desired speed ratio id and the actual speed ratio i, and throttle opening. It is seen from the simulation results that the CVT shift speed is determined by the dynamic shift control strategy to provide appropriate performance and comfort for the driver's demand and driving condition. Additionally, experiments are performed to investigate the dynamic performance of the shift speed for the lift foot up. From the experimental results, it is found that improved shift feeling can be obtained by the dynamic shift control strategy when lift foot up occurs.

• 한국자동차공학회논문집
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• 제7권8호
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• pp.233-247
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• 1999

Traffic accidents are normally caused by late or faulty judgements due to the driver's inaccurate estimation of the distance, velocity, and acceleration from the surrounding vehicles as well as his carelessness or inattention. Thus, the development of collision avoidance systems is motivated by their great potential for increased vehicle safety. A typical collision avoidance system consists of the forward-looking sensor, the criteria for activation of collision warming and avoidance, the collision avoidance maneuvers, and the user interface. This thesis is concerned with the development of a collision warning algorithm in which the driver is warned of approaching collision with the visual and/or the audible signals . The warning algorithm based on fuzzy logic is presented here based on new warning criteria. It has been newly derived from the conventional warning equation by adding a new input variable of the required deceleration to avoid collision. The algorithm is also able to adapt to the individual driver's taste along with the different road conditions by externally controlling the warning intensity. Finally , the proposed algorithm has been validated using computer simulation.

• 한국철도학회논문집
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• 제12권3호
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• pp.342-347
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• 2009

고장모드, 영향 및 임계분석(FMECA)은 시스템의 구성요소가 갖는 잠재적인 고장모드와 각 고장모드가 시스템에 미치는 영향을 평가하는 도구로 활용된다. 일반적으로 FMECA는 관련 전문가들의 의견에 따라 고장모드의 심각도와 치명도를 평가하여 이를 위험도 매트릭스의 양축으로 나타냄으로써 중요한 고장모드에 대한 분석을 수행한다. 그러나 이러한 절차는 평가가 전문가의 주관에 의해 이루어져 결과에 불확실성이 포함될 수밖에 없다. 따라서 본 논문에서는 최소절단집(MCS)와 퍼지이론을 이용한 새로운 FMECA 절차를 제안한다. 심각도 평가에 있어서는 MCS를 이용함으로써 객관적인 구조적 중요도를 평가할 수 있게 하였고, 치병도의 평가에서는 설비의 대표적인 고장률을 이용하였다. 그리고 두 지수를 종합하기 위해 퍼지 전문가 시스템을 구성하여 종합적인 위험도를 평가하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.685-688
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• 1995

In this paper we proposed new scheme replacing adaptive mechanism part in MRAC by fuzzy logic in order to improve transient response in adaptive control system. Conventional adaptive control system has good performance in steady state but it has large error or problem with rise time in transient state. We need to increase adaptation gain of control variable but it causes robustness problem that makes ststem unstable for set-point, load-variation, and dynamic change. To demonstrate presented FTAC(fuzzy tunning adaptive control)'s superiority, presented method is introduced for a class of SISO systems and compare with MRAC. By analyzing simulation result, we can see transient response is improved and the system is not affected by disturbance in proposed method in comparison to MRAC.

• 한국지능시스템학회논문지
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• 제18권4호
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• pp.488-493
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• 2008

본 논문은 연속 주조 공정에서의 용강 높이에 대한 수학적인 비선형모델을 유도하는데, 여기에는 용강 높이, 몰드내의 입출력 유량, 스토퍼의 위치와 입력유량의 관계 등이 고려되었다. 비선형 모델은 MATLAB을 사용하여 구현되었으며 실제 데이터와 비교하여 수학적 모델이 유효함을 확인하였다. 구현된 비선형 모델을 사용하여, 퍼지 시스템에 의하여 변화하는 $K_p$값을 가지는 퍼지 PI 제어기를 사용하여, 기존에 사용되던 PI 제어기보다 나은 제어 성능 및 외란에의 강인성을 가짐을 시뮬레이션으로 보였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.32-34
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish 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 is proposed model reference adaptive fuzzy control(MFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaption mechanism(FAM), MFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, MFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 춘계학술대회 논문집
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• pp.416-419
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under-parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of loaming through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive loaming mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control(FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 춘계학술대회 논문집
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• pp.404-407
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish 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 is proposed adaptive fuzzy controller(AFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaptation mechanism(FAM), AFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, AFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.