• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.8
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• pp.938-946
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• 1992

A novel 2-dimensional matched filter of the parallel-jaw type using fuzzy logic is proposed for bin picking. Specifically, the averaged pixel intensity of the windowed region for the filtering is considered to be fuzzy. Also membership functions for darkness and brightness are designed by employing the intensity histogram of the image. Then a rule is given to know how much a windowed region can be a possible holdsite. Furthermore eight rules are made to determine the part orientation, where Mamdani's reasoning method is applied. The proposed technique shows better performances than that of the conventional matched filtering technique in the following senses` 1) most of holdsites determined by the proposed technique are not concentrated at the locations nearly the end of part and 2) our filter is rather insensitive to noises than the conventional method. To show the validities of our proposed technique, some experimental results are illustrated and compared with the results by conventional matched filter technique.

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1880-1893
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• 1996

In this paper, we propose the fuzzy traffic control method in ABR service for the effective use of ATM link. This method, a modified version of EPRCA which is one of rate control methods in ABR service, controls the values of the transmission rates of source by using the fuzzy traffic inference based on switch buffer size and buffer variate rate. For this method, we developed a model and algorithm of the fuzzy traffic control method and a fuzzy traffic controller, after studying fuzzy and neural networks which applied to ATM traffic control and EPRCA. For the fuzzy traffic controller, we also designed a membership function, fuzzy control rules and a max-min inferencing method. We conducted a simulation and compared the link utilization of the fuzzy traffic control method with that of the EPRCA method. The results of the simulation indicated that, compared to EPRCA, the fuzzy traffic control method improves the link utilization by 2.3% in a normal distribution model and by 2.7% in the MMPP model of the source.

• Journal of Navigation and Port Research
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• v.31 no.8
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• pp.697-703
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• 2007

In this paper, we focuses on the development of Takagi-Sugeno (T-S) fuzzy modeling in a nonlinear container crane system. A T-S fuzzy model is characterized by fuzzy "if-then" rules which represent the locally input-output relationship whose consequence part is described by a state space equation as subsystem. The T-S fuzzy model in container cranes first obtains a few number of linear models according to operation conditions and blends these conditions using fuzzy membership functions. Parameters of the membership functions are adjusted by a RCGA to have same dynamic characteristics with nonlinear system of a container crane. Simulations are given to illustrate the performance of T-S fuzzy model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.9
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• pp.1727-1736
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• 2006

In a fuzzy control system to vocess fuzzy data in high-speed for intelligent systems, one of the important problems is the improvement of the execution speed in the fuzzy inference and defuzzification stages. Especially, it is more important to have high-speed operations in the consequent Pan and defuzzification stage. Therefore, in this paper, to improve the speedup of the fuzzy controllers for intelligent systems, we propose novel integer fuzzy operation method without mulitplications and divisions by only integer addition to convert real values in the fuzzy membership functions in the consequent part to integer grid pixels $(400{\times}30)$ without [0, 1] real operations. Also we apply the proposed system to the truck backer-upper control system. As a result, this system shows a real-time very high speed fuzzy control as compared as the conventional methods. This system will be applied to the real-time high-speed intelligent systems such as robot arm control.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.1
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• pp.102-108
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• 2010

The T-S fuzzy model of a ship is made from the nonlinear extension of Nomoto's 2nd-order model as the previous step before designing of the fuzzy type autopilot to consider the design specifications and the economic efficiency. The T-S fuzzy model is considered as a design variable of the heading angular velocity of ship. The linear models will be combined as "IF-THEN" fuzzy rules after get in this one area of the linear model(sub-system) by change of the heading angular velocity of a ship. The dynamic characteristic of a ship with the parameters of linear models and fuzzy membership functions are estimated to match by using the model adjustment technic with input/output data and a RCGA.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.8
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• pp.1104-1110
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• 2012

The inverted pendulum system is a common, interesting control problem that involves many basic elements of control theory. In the early, controls of stabilization for the inverted pendulum system were used classical methods like PD, PID controller. In recently, however, control methods based on modern and intelligent control theory are widely applied. The fuzzy logic controller which is often used in nonlinear control is a little too hard to design due to increasing fuzzy rules rapidly if the given system like inverted pendulum has many state variables. Also, in case the state variables are divided into two parts, two fuzzy controllers are needed in the control system. In this paper, the authors propose FCSC(Fuzzy Controller based on State variables Combination) that reorganized into two new signals depending on the physical meaning of the four state variables of the inverted pendulum system. The proposed method is applied to the inverted pendulum system and simulations are accomplished to illustrate the control performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.524-528
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• 1996

Quality information is known to have the characteristic of continuous distribution in many manufacturing processes. It is difficult to describe the process condition by classifying the distribution into discrete ranges which is based on the set concept. Fuzzy control chart has been developed for the control of linguistic data but it still utilizes the dichotomous notion of classical set theory. In this paper, the fuzzy sampling method is studied in order to manage the ambiguous data properly and incorporated for generating fuzzy control chart. The method is based on the fuzzy set concept and considered to be appropriate for the realization of a complete fuzzy control chart. The fuzzy control chart was compared with the conventional generalized p-chart in the sensitivity for quality distribution and robustiness against the noise. The fuzzy control chart with the fuzzy sampling method showed better characteristics.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.490-490
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• 2022

국내 대하천 및 중·소규모 하천의 홍수터 공간을 활용하여 체육시설 및 공원 등과 같은 친수 시설물을 조성하여 친수공간으로 활용하고 있으며, 시민들의 친수활동 빈도는 증가추세에 있다. 특히 하천 내에서 수상 레크레이션 활동 등과 같은 다양한 친수활동이 증가하고 있으며, 하천친수에 관한 정보 수요가 급증하고 있으나 체계적인 공급은 미흡한 수준이다. 따라서 본 연구에서는 친수공간 조성 및 유지관리에 대한 측면과 친수공간에서의 쾌적한 친수활동을 위한 정보제공 목적으로 하천 친수공간에서의 복합모니터링을 이용한 친수활동 종합지수를 산정 방법을 개발하고자 하였다. 센서 기반의 시계열 데이터 구축을 위해 하천 수질, 수리인자의 복합모니터링을 진행하였다. 수리인자(수위, 유속, 수면폭 등)와 수질인자(탁도, Chl-a, pH 등), 기상학적 인자(자외선 지수, 미세먼지 등) 등급에 따른 허용기준을 설정하여 각 등급 별로 수리인자의 값을 0~1 사이 값인 소속도로 변환하여 소속도의 합성 및 친수활동 등급을 결정하였다. 최종적으로 수리, 수질, 기상 인자별 소속도 함수 산정을 통한 퍼지합성 이론 기반의 친수활동 종합지수를 산정하였다. 그리고 친수활동 종합지수를 예보하기 위한 모델 적용을 위한 방향성을 정립하였다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.25-31
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• 2011

Principal component analysis (PCA) is a well-known method for dimensionality reduction and feature extraction. Although PCA has been applied in many areas successfully, it is sensitive to outliers due to the use of sum-square-error. Several variants of PCA have been proposed to resolve the noise sensitivity and, among the variants, improved robust fuzzy PCA (RF-PCA2) demonstrated promising results. RF-PCA2, however, still can fall into a local optimum due to equal initial membership values for all data points. Another reason comes from the fact that RF-PCA2 is based on sum-square-error although fuzzy memberships are incorporated. In this paper, a variant of RF-PCA2 called RF-PCA3 is proposed. The proposed algorithm is based on the objective function of RF-PCA2. RF-PCA3 augments RF-PCA2 with the objective function of PCA and initial membership calculation using data distribution, which make RF-PCA3 to have more chance to converge on a better solution than that of RF-PCA2. RF-PCA3 outperforms RF-PCA2, which is demonstrated by experimental results.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.1
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• pp.109-115
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• 2010

This paper deals with trajectory control of computer simulated mobile robot via fuzzy control. Mobile robot is controlled by Mamdani type fuzzy controller. Inputs of the fuzzy controller are angle between mobil robot and target, changed angle and output is the steering angle, which is control input. Fuzzy rules have seven rules and are selected by human experiential knowledge. Also we propose a scaling factors tuning scheme which is the another focus in designing fuzzy controller. In this paper, we adapt the RCGA which is well known in parameter optimization to adjust scaling factors. The simulation results show that the fuzzy control effectively realize trajectory stabilization of the mobile robot along a given reference target from various initial steering angles.