• 한국지능시스템학회논문지
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• 제1권1호
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• pp.9-25
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• 1991

This tutorial paper has been written for biologists, physicians or beginners in fuzzy sets theory and applications. This field is introduced in the framework of medical diagnosis problems. The paper describes and illustrates with practical examples, a general methodology of special interest in the processing of borderline cases, that allows a graded assignment of diagnoses to patients. A pattern of medical knowledge consists of a tableau with linguistic entries or of fuzzy propositions. Relationships between symptoms and diagnoses are interpreted as labels of fuzzy sets. It is shown how possibility measures (soft matching) can be used and combined to derive diagnoses after measurements on collected data. The concepts and methods are illustrated in a biomedical application on inflammatory protein variations. In the case of poor diagnostic classifications, it is introduced appropriate ponderations, acting on the characterizations of proteins, in order to decrease their relative influence. As a consequence, when pattern matching is achieved, the final ranking of inflammatory syndromes assigned to a given patient might change to better fit the actual classification. Defuzzification of results (i.e. diagnostic groups assigned to patients) is performed as a non fuzzy sets partition issued from a "separating power", and not as the center of gravity method commonly employed in fuzzy control. It is then introduced a model of fuzzy connectionist expert system, in which an artificial neural network is designed to build the knowledge base of an expert system, from training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the connections: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through MIN-MAX fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feed forward network is described and illustrated in the same biomedical domain as in the first part.

• 정보처리학회논문지B
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• 제16B권6호
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• pp.463-470
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• 2009

본 논문은 기존의 센서 기반 화재 감지기가 넓은 장소와 개방된 공간에서 성능이 저하되는 단점을 보완하기 위하여 카메라 영상을 이용한 화재 불꽃 감지 알고리즘을 제안한다. 기존의 연구에서는 다수의 휴리스틱한 정보를 이용하거나 속도가 느린 문제점을 보여주었다. 이를 해결하기 위하여, 통계적인 값들을 사용했으며 속도를 개선하기 위해 블록 단위로 처리하였다. 먼저 입력된 영상에서 배경 모델과 불꽃 색상 모델 을 이용하여 화재 후보 영역을 추출한다. 그 후 후보 블록에 대하여 시간축 상에서의 명도 변화, 웨이블릿 계수 변화, 모션 변화를 추출하여 확 률 모델을 생성하며, 생성된 모델들을 퍼지 로직의 멤버십 함수로 사용하였다. 마지막으로 역퍼지(defuzzification) 과정을 통해 최종 결과 함수를 생성하고 이로부터 불꽃 발생 확률값을 예측하였다. 실험에서는 제안한 화재 불꽃 감지 알고리즘을 성능이 가장 좋다고 알려진 Toreyin의 알고리즘과 비교하여 성능이 개선되었음을 보여주고 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.60-64
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• 1997

Designing fuzzy controller, there are difficulties that we have to determine fuzzy rules and shapes of membership functions which are usually obtained by the amount of trial-and-error or experiences from the experts. In this paper, to overcome these defects, genetic algorithms which is probabilistic search method based on genetics and evolution theory are used to determine fuzzy rules and fuzzy membership functions. We design a series compensation fuzzy controller, then determine basic structures, input-output variables, fuzzy inference methods and defuzzification methods for fuzzy controllers. We develop genetic algorithms which may search more accurate optimal solutions. For evaluating the fuzzy controller performances through experiments upon an actual system, we design the fuzzy controllers for the speed control of a DC series motor with nonlinear characteristics and show good output responses to reference inputs.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.516-519
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• 1997

In this paper, the control of the temperature for the vehicle air conditioner is implemented with the fuzzy controller using a micro controller. The linguistic control rules of the fuzzy controller are separated into two out variables(multi input multi output ; MIMO) : one is those for the blower motor, and the other is those for air mix door. The error in fuzzy controller, the input variable is defined as difference between the reference temperature and the actual temperature in the cabin room. The fuzzy control rules are established from the human operator experience, and based engineering knowledge about the process. The method of the center of gravity is utilized for the defuzzification.

• 전자공학회논문지B
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• 제31B권7호
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• pp.149-158
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• 1994

Recently the fuzzy control is widely used as a tool for constructing automatic control systems which can replace the manual operation of large-scale nonlinear plants. In most applications of the fuzzy control however it is hard to meet the requirement of the operation time. In some real-time control the fuzzy control scheme requires too much computing time for fuzzification inference and defuzzification. To reduce the computing time there may be two alternatives the development of a new operation algorithm and the design of high-speed fuzzy hardware. In this paper to solve the problem of reducing the fuzzy operation time we propose a new high-speed fuzzy hardware scheme which has merits of its generality and extensibility. Finally we verify the proposed fuzzy hardware.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.82-85
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• 2004

This paper proposes the development of delay compensator to minimize performance degradation caused by time delays in network-based real-time control systems. The delay compensator uses the time-stamp method as a direct delay measuring method to measure time delays generated between network nodes. The delay compensator predicts the network time delays of next period in the views point of time delays and minimizes performance degradation from network through considering predicted time delays. Control output considering network time delays is generated by the defuzzification of probable time delays of next period. The time delays considered in the delay compensator are modeled by using a timed Petri net model. The proposed delay prediction mechanism for the delay compensator is evaluated through some simulation tests by measuring deviation of the predicted delays from simulated delays.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.676-678
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• 2003

Microtunneling techniques play a crucial role in the construction of pipelines. This paper shows the automatic tunneling algorithm of microtunneling system using fuzzy logic technology to assist operators to assure the quality of microtunneling construction. To have effective output value of fuzzy controller, we slightly modified the conventional defuzzification methods. The proposed automatic tunneling algorithm shows good tunneling results comparable with those of experts.

• 한국융합학회논문지
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• 제4권4호
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• pp.31-40
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• 2013

PID auto-tuning controller was designed via fuzzy logic. Typical values such as error and error derivative feedbackwere changed as heuristic expressions, and they determine PID gain through fuzzy logic and defuzzification process. Fuzzy procedure and PID controller design were considered separately, and they are combined and analyzed. Obtained auto-tuning PID controller by Fuzzy Logic showed the ability for less than 3rd order plant control.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.189-193
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• 1998

A PID type fuzzy Controller is proposed based on a crisp type model in which the consequent parts of the fuzzy control rules are functional representation or real numbers. Using the conventional PID control theory, a new PID type fuzzy controller is developed, which retains the characteristics of the conventional PID controller. An advantage of this approach, is that it simplifies the complicated defuzzification algorithm which could be time consuming. Computer simulation results have shown that the proposed PID fuzzy controller has satisfactory tracking performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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• pp.50-55
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• 2004

We propose an intgrated Gill environment system having only integer fuzzy operations in the consequent part and the defuzzification stage. In this paper, we also propose an integrated Gill environment system with 4 parallel fuzzy processing units to be operated in parallel on the classification of the sensed image data. In this, we solve the problems of taking longer times as the fuzzy real computations of [0, 1] by using the integer pixel conversion algorithm to convert lines of each fuzzy linguistic term to the closest integer pixels. This procedure is performed automatically in the GUI application program. As a Gill environment, PCI transmission, image data pre-processing, integer pixel mapping and fuzzy membership tuning are considered. This system can be operated in parallel manner for MIMO or MISO systems.