• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.169-171
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• 1999

This paper presents a new demand control technique using fuzzy logic. Generally, predictive demand control method often brings about a large number of control actions and undesirable alarm during the beginning stage of the demand period. To solve this problem, a fuzzy predictive algorithm is proposed. The main idea of the method is the determination of sensitivity factor by using fuzzy logic. The performance of the proposed algorithm is tested through a case study.

• 한국지진공학회논문집
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• 제8권4호
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• pp.51-62
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• 2004

사장교의 지진응답 제어를 위한 퍼지관리제어기법에 대하여 연구하였다. 제시하는 방법은 복합제어방법의 하나로서, 여러 개의 최적제어기로 이루어진 하부제어기와 퍼지관리자로 구성되는 계층적인 구조를 가진다. 하위제어기들은 사장교의 주요 지진응답들을 저감시키도록 각각 독립적으로 설계되며, 퍼지관리자는 설계된 하위제어기들의 참여율을 조절함으로써 향상된 제진성능을 확보한다. 이는 하위제어기의 정적 제어이득을 퍼지추론과정에 기반하여 실시간으로 변화하는 동적 제어이득으로 변화함으로써 이루어진다. 제안하는 방법으리 적용성을 평가하기 위하여 Dyke 등이 제안한 사장교의 벤치마크 제어문제를 설계 예로 고려하였으며, 사장교 지진응답제어를 위한 제어변수로는 주탑하부의 전단력과 휨모멘트, 주탑상부의 수평변위 및 테크 주탑간 상대변위, 그리고 케이블의 장력을 선정하였다. 벤치마크 사장교에 대하여 제안한 퍼지관리제어기 및 최적제어이론에 기반한 LQG 제어기의 제어성능 비교로부터 제시하는 기법의 효율성을 검증하였다.

• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.671-676
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• 2007

In this paper, a novel neuro-fuzzy controller is presented. The generic fuzzy controller is compensated by a neural network controller so that an overall control structure forms a neuro-fuzzy controller. The proposed neuro-fuzzy controller solves the difficulty of selecting optimal fuzzy rules by providing the similar effect of modifying fuzzy rules simply by changing crisp input values. The performance of the proposed controller is tested by controlling humanoid robot arms. The humanoid robot arm is analyzed and implemented. Experimental studies have shown that the performance of the proposed controller is better than that of a PID controller and of a generic fuzzy PD controller.

• 한국지진공학회논문집
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• 제5권4호
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• pp.75-81
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• 2001

지진하중을 받는 구조물의 능동제어를 위한 퍼지관리제어기법(fuzzy supervisory control technique)에 관하여 연구하였다. 제시하는 제어기법은, 구조물에 발생하는 변위 및 속도 등의 정보를 이용하여 퍼지추론과정을 거쳐서 구조물의 상태를 파악함으로써 기설계된 제어이득들을 실시간으로 관리 및 조정한다. 알고리즘의 검증을 위하여 지진하중을 받는 3자유도 구조물에 대하여 수치모사를 수행하여 정적이득을 갖는 LQR제어기와 비교하였으며, 해석결과 제시한 제어기는 지진응답의 제어에 매우 효과적임을 알 수 있다.

• 한국측량학회지
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• 제20권3호
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• pp.273-282
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• 2002

GIS는 다양한 영역에서 유용한 도구로서 자리잡고 있으나, 한편으로는, 복잡한 문제를 해결하기 위해서는 GIS가 수학, 공학적인 모델링툴과 결합되는 것이 필요하다는 견해와 연구결과가 등장하고 있다. LP(Linear Programming)는 주어진 자원을 최적으로 배분하는 문제에 사용되는 수학적인 기법이다. LP는 공간적인 표현을 포함하지 않기때문에 GIS의 기능들과 결합될 때 그 유용성이 높아질 수 있다. 그러나 전통적인 LP는 명료하게 조건이 주어질 경우에만 적합한 방법이므로, 토지이용계획과 같이 결정요소가 명확한 값으로 주어질 수 없는 경우에는 현실적으로 적용하기 어려워진다. 이 연구에서는, 이와 같이 불명료한(fuzzy) 상황을 다루기 위해 Fuzzy logic을 사용한 fuzzy-LP를 개발하고, 이를 GIS와 통합하는 방법론을 제시한다. 통합시스템에서 GIS는 Fuzzy-LP과정으로 데이터를 공급하거나 Fuzzy-LP의 결과값을 표현하는데 이용된다. 이 시스템을 토지이용배분문제에 적용하는 경우를 예시하였다.

• International Journal of Reliability and Applications
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• 제12권2호
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• pp.79-94
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• 2011

Redundancy-reliability allocation problems in multi-stage series-parallel systems are addressed in this study. Fuzzy programming techniques are proposed for finding satisfactory solutions. First, a multi-objective programming model is formulated for simultaneously maximizing system reliability and minimizing system total cost. Due to the nature of uncertainty in the problem, the fuzzy set theory and technique are used to convert the deterministic multi-objective programming model into a fuzzy nonlinear programming problem. A heuristic method is developed to get satisfactory solutions for the fuzzy nonlinear programming problem. A Pareto optimal solution is found with maximal degree of satisfaction from the interception area of fuzzy sets. A case study that is related to the electronic control unit installed on aircraft engine over-speed protection system is used to implement the developed approach. Results suggest that the developed fuzzy multi-objective programming model can effectively resolve the fuzzy and uncertain problem when design goals and constraints are not clearly confirmed at the initial conceptual design phase.

• 한국정밀공학회지
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• 제21권4호
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• pp.202-209
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• 2004

Quality control is essential to the final product in BGA-type PCB fabrication. So, many automatic vision systems have been developed to achieve speedy, low cost and high quality inspection. A multiple threshold selection algorithm is a very important technique for machine vision based inspection. In this paper, an inspected image is modeled by using fuzzy sets and then the parameters of specified membership functions are estimated to be in maximum fuzzy entropy with the probability of the fuzzy sets, using the exhausted search method. Fuzzy c-partitions with the estimated parameters are automatically generated, and then multiple thresholds are selected as the crossover points of the fuzzy sets that form the estimated fuzzy partitions. Several experiments related to flip chip BGA images show that the proposed algorithm outperforms previous ones using both entropy and variance, and also can be successfully applied to AVI systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.1047-1051
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• 1993

A fuzzy controller of a manipulator with artificial rubber muscles is proposed. The fuzzy logic controller as a compensator is described to control the trajectory tracking of a -two link manipulator, where computed torque control method has already assumed to be applied. We shows that the fuzzy compensator with a simple adaptive scaling technique is effective for the robust control when there exist model uncertainties and/or untuned feedback gains. The effectiveness of the proposed control method is illustrated by some experimental results for a circular path tracking.

• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1114-1117
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• 1993

The paper presents an effective method for finding the propagation structure of the real origin of a system malfunction. It uses a combined system model consisting of Structural Model (SM) in the form of Fuzzy Directed Graph and Behavior Model (BM) as a set of Fuzzy Relational Equations $A\;{\circ}\;R\;=\;B$. Here a specially proposed fuzzy inference technique is checked and investigated. Finally a test example for fault diagnosis of an industrial system is given and analyzed.