• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.225-228
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• 2002

When the fuzzy logic controller (FLC), which is designed based on the plant model, is applied to the real control system, satisfactory control performance may not be attained due to modeling errors from the plant model. In such cases, the control parameters of the controller must be adjusted to enhance control performance. Until now, the trial and error method has been used, consuming much time and effort. To resolve such problem, response surface methodology (RSM), a new method of adjusting the control parameters of the controller, is suggested. This method is more systematic than the previous trial and error method, and thus optimal solutions can be provided with less tuning. First, the initial values of the control parameters were determined through the plant model and the optimization algorithm. Then, designed experiments were performed in the region around the initial values, determining the optimal values of the control parameters which satisfy both the rise time and overshoot simultaneously.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2373-2378
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• 2005

An emotion detection algorithm using frontal facial image is presented in this paper. The algorithm is composed of three main stages: image processing stage and facial feature extraction stage, and emotion detection stage. In image processing stage, the face region and facial component is extracted by using fuzzy color filter, virtual face model, and histogram analysis method. The features for emotion detection are extracted from facial component in facial feature extraction stage. In emotion detection stage, the fuzzy classifier is adopted to recognize emotion from extracted features. It is shown by experiment results that the proposed algorithm can detect emotion well.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.480-482
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• 1998

Sliding mode is a robust control method and can be applied in the presence of model uncertainties and parameter disturbances. This study shows that the proposed fuzzy sliding mode control could reduce chattering problemed in sliding mode control. In this paper, an inverted pendulum is effectively controlled by the fuzzy sliding control technique. To reduce movable region of the inverted pendulum body, the angle and its integrated quantity are applied to the controller. The effectiveness of result is shown by the simulation and the experimental test for the inverted pendulum.

• Nuclear Engineering and Technology
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• v.30 no.3
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• pp.222-234
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• 1998

The Westinghouse OT$\Delta$T DNB protection logic heavily restricts the operation region by applying the same logic for a full range of operating pressure in order to maintain its simplicity. In this work, a fuzzy neural network method is used to estimate the DNB protection limit using the measured average temperature and pressure of a reactor core. Fuzzy system parameters are optimized by a hybrid learning method. This algorithm uses a gradient descent algorithm to optimize the antecedent parameters and a least-squares algorithm to solve the consequent parameters. The proposed method is applied to Yonggwang 3&4 nuclear power plants and the proposed method has 5.99 percent larger thermal margin than the conventional OT$\Delta$T trip logic. This simple algorithm provides a good information for the nuclear power plant operation and diagnosis by estimating the DNB protection limit each time step.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.994-996
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• 2000

Switched reluctance motor generally operates in the magnetically saturated region because the saturation gives several benefits to its performance. This paper investigates the modelling and fuzzy tuning PI control of a nonlinear switched reluctance motor. The modelling is performed through neural network technique. Fuzzy auto-tuning PI control is designed for a robust performance in load and speed variations. Simulation and experimental results indicate better performances compared with simple PI control.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.3
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• pp.445-452
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• 2010

Adequate segmentation of target objects from the background plays an important role for the performance of automatic target recognition(ATR) system. This paper presents a new segmentation algorithm using fuzzy thresholding to extract a target. The proposed algorithm consists of two steps. In the first step, the region of interest(ROI) including the target can be automatically selected by the proposed robust method based on the frame difference of each image sensor. In the second step, fuzzy thresholding with a proposed membership function is performed within the only ROI selected in the first step. The proposed membership function is based on the similarity of intensity and the adjacency of target area on each image. Experimental results applied to real CCD/IR images show a good performance and the proposed algorithm is expected to enhance the performance of ATR system using multi-sensors.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2908-2910
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• 1999

In this paper, a fuzzy model is identified and optimized using the hybrid algorithm and HCM clustering method. Here, the hybrid algorithm is carried out as the structure combined with both a genetic algorithm and the improved complex method. The one is utilized for determining the initial parameters of membership function, the other for obtaining the fine parameters of membership function. HCM clustering algorithm is used to determine the confined region of initial parameters and also to avoid overflow phenomenon during auto-tuning of hybrid algorithm. And the standard least square method is used for the identification of optimum consequence parameters of fuzzy model. Two numerical examples are shown to evaluate the performance of the proposed model.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.498-500
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• 1993

This paper presents handover algorithm method using fuzzy rules and neura1 network. In future mobile communication systems, the amount of call requests over a region will increase dramatically. This problem has to be solved by decreasing the cell size. But, this method lets a mobile station switch the a base station at a higher rate. In order to maintain better mobile communication system in a micro or pico cellular system, better handover algorithm must be devoloped. In this paper, we propose a handover algorithm which is based on the fuzzy teory that is applied to make rules with the parameters and neural network that is to learn rules. This new handover algorithm is tested by computer simulation and compared with the conventional algorithms.

• Membrane and Water Treatment
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• v.10 no.2
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• pp.149-154
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• 2019

The information matter-element system was built to assess safety of water source. Based on the thought of multiindex fusion, fuzzy matter-element model evaluating water source behavior was constructed by matter-element transform. This model can process comprehensively hydrogeological data, ecological environment, water pollution, surface disturbance, and so on. Water source safety behavior can be described by the qualitative and quantitative manners. According to the development trend of quantitative results, water source safety behavior can be expressed dynamically. As an example, the proposed method was used to assess safety status of 7 water sources in the region. The numerical example shows that the proposed method is feasible and effective, and the evaluation results are reasonable.

• Journal of Korea Multimedia Society
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• v.25 no.5
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• pp.670-675
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• 2022

This study proposes an improved binarization method to improve image recognition rate. The research goal is to minimize the information loss that occurs during the binarization process, and to transform the object of the original image that cannot be determined through the transformation process into an image that can be judged. The proposed method uses a stepwise segmentation method of an image and divides blocks using prime numbers. Also, within one block, a trapezoidal type of fuzzy is applied. The fuzzy trapezoid is binarized by dividing the brightness histogram area into three parts according to the degree of membership. As a result of the experiment, information loss was minimized in general images. In addition, it was found that the converted binarized image expressed the object better than the original image in the special image in which the brightness region was tilted to one side.