• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.1127-1128
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• 2008

In this paper, we propose a control method to improve control performance for a Quad-rotor Unmanned Aerial Vehicle's stabilization. The proposed method is the Fuzzy+I control that contains a fuzzy controller which processes signals from the error and the change of error, and generates the control signal by summing up fuzzy output signal and integral signal. We simulated and experimented on the fuzzy+I control method by implementing Quad-rotor UAV that is able to hovering, for the purpose of verifying the effectiveness of the proposed fuzzy+I control method in comparison with general PID control, and we found out that fuzzy+I controller improved control performance of the system.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 추계종합학술대회
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• pp.1003-1006
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• 2003

본 논문에서는 유전자 알고리즘을 이용한 자동 퍼지규칙 추출 방식을 제안한다. 제안한 방식은 전문가의 조언에 의한 퍼지규칙 기반이나 시행착오법에 의한 퍼지규칙에 의존하지 않고 유전자 알고리즘을 이용한 자동 퍼지규칙 방식이다. 제안한 방식의 유용성을 확인하기 위해 dc모터제어에 적용하였으며 유용성을 확인하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.220-226
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• 2002

In this paper, we develop the intelligent digitally redesigned fuzzy controller for nonlinear systems. Takagi-Sugeno (TS) fuzzy model is used to model the nonlinear systems and a continuous-time fuzzy-model-based controller is designed based on the extended parallel-distributed-compensation(EPDC) method . The digital controllers are determined from existing analogue controllers. The proposed method provides an accurate and effective method for digital control of continuous-time nonlinear systems and enables us to efficiently implement a digital controller via the pre-determined continuous-time 75 fuzzy-model-based controller. We have applied the proposed method to the duffing forced oscillation system to show the effectiveness and feasibility of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2393-2398
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• 2003

In this paper, we proposes a new fuzzy inference system for modeling nonlinear systems given input and output data. In the suggested fuzzy inference system, the number of fuzzy rules and parameter values of membership functions are automatically decided by using the kernel-based method. The kernel-based method individually performs linear transformation and kernel mapping. Linear transformation projects input space into linearly transformed input space. Kernel mapping projects linearly transformed input space into high dimensional feature space. The structure of the proposed fuzzy inference system is equal to a Takagi-Sugeno fuzzy model whose input variables are weighted linear combinations of input variables. In addition, the number of fuzzy rules can be reduced under the condition of optimizing a given criterion by adjusting linear transformation matrix and parameter values of kernel functions using the gradient descent method. Once a structure is selected, coefficients in consequent part are determined by the least square method. Simulated result illustrates the effectiveness of the proposed technique.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.524-526
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• 1999

In the construction of successful fuzzy models and/or controllers for nonlinear systems, the identification of a good fuzzy inference system is an important yet difficult problem, which is traditionally accomplished by a time-consuming trial-and-error process. In this paper, we propose a systematic identification procedure for complex multi-input single-output nonlinear systems with DNA coding method. A DNA coding method is optimization algorithm based on biological DNA as conventional genetic algorithms(GAs) are. The strings in the DNA coding method are variable-length strings, while standard GAs work with a fixed-length coding scheme. the DNA coding method is well suited to learning because it allows a flexible representation of a fuzzy inference system. We also propose a new coding method fur applying the DNA coding method to the identification of fuzzy models. This coding scheme can effectively represent the zero-order Takagi-Sugeno(TS) fuzzy model. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its application to a Duffing-forced oscillation system.

• Journal of Advanced Marine Engineering and Technology
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• 제28권2호
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• pp.200-209
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• 2004

The fuzzy control based on $\alpha$-level fuzzy set decomposition. It is known to produce quick response and calculating time of fuzzy inference. This paper derived the embodiment computational algorithm for defuzzification by min-max fuzzy inference and the center of gravity method based on $\alpha$-level fuzzy set decomposition. It is easy to realize the fuzzy controller hardware. based on the calculation formula. In addition. this study proposed a circuit that generates PWM actual signals ranging from fuzzy inference to defuzzification. The fuzzy controller was implemented with mixed analog-digital logic circuit using the computational fuzzy inference algorithm by min-min-max and defuzzification by the center of gravity method. This study confirmed that the fuzzy controller worked satisfactorily when it was applied to the position control of a dc servo system.

• 한국정보통신학회논문지
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• 제5권7호
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• pp.1374-1383
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• 2001

기존의 제어방식 보다 강인성이 우수한 퍼지 논리 제어방식에서 최적화되지 않은 제어규칙을 이용하여, 오프라인 상에서 소속함수 관계와 스케일링 팩터를 유전자알고리즘으로 최적화한 후, 온라인으로 퍼지제어기를 구성하는 제어방식을 제안하였다. 제안한 방식을 단일 링크 매니률레이터의 추종제어에 적용하여 기존 퍼지제어 방식과 비교 검토한 결과 퍼지제어규칙의 수도 감소하고 제어성능도 우수함을 확인하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권3호
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• pp.161-165
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• 2009

Increase of multimedia information in Web requires a new method to manage and service multimedia documents efficiently. This paper proposes a conceptual object grouping method by fuzzy filtering, which is automatically constituted based on increase of multimedia documents. The proposed method composes subsumption relations between conceptual objects automatically using fuzzy filtering of the document objects that are extracted from domains. Grouping of such conceptual objects is regarded as subsumption relation which is decided by $\mu$-cut. This paper proposes $\mu$-cut, FAS(Fuzzy Average Similarity) and DSR(Direct Subsumption Relation) to decide fuzzy filtering, which groups related document objects easily. This paper used about 1,000 conceptual objects in the performance test of the proposed method. The simulation result showed that the proposed method had better retrieval performance than those for OGM(Optimistic Genealogy Method) and BGM(Balanced Genealogy Method).

• 한국정보처리학회논문지
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• 제3권7호
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• pp.1880-1893
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• 1996

본 논문에서는 ATM 링크의 이용을 향상을 위해 ABR 서비스에서의 퍼지 트래픽 제어 방식을 제안한다. 제안된 방식은 ABR 서비스에서 전송률 제어 방식인 EPRCA를 개선한 것으로써 송신원의 전송률 제어값을 스위치단의 버퍼량과 버퍼 별화율로 퍼지 추론을 실시하여 얻는 방식이다. 본 논문에서는 ATM 트래픽 제어에 적용된 퍼지, 신경 망의 경우와 ATM의 ABR 서비스 제어 방식인 EPRCA 방식을 알아본 후, 퍼지 트래픽 제어 방식의 모형과 알고리즘, 퍼지 트래픽 제어기 등을 연계한다. 퍼지 트래픽 제어 기에서는 사용 소속함수, 퍼지 제어 규칙,max-min 추론 방법 등을 설계한다. 본 논문 에서 제안된 방식은 모의 실험을 통해 기존의 EPRCA 방식과 퍼지 트래픽 제어방식의 링크 이용율을 비교·분석함으로써 그 우수성을 검증한다. 모의 실험 결과 퍼지 트래 픽 제어 방식이 EPRCA 방식보다 송신원의 정규 분포 모델의 경우 2.3%, MMPP 모델의 경우 2.7%의 링크 이용률 개선을 얻었다.

• 한국경영과학회지
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• 제12권2호
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• pp.21-35
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• 1987

This paper presents a method for propagating fuzzy concepts through fuzzy IF-THEN-ELSE rules. A fuzzy IF-THEN-ELSE rule consists of a set of fuzzy condition and conclusion pairs. These pairs assumed to contain informations about a fuzzy mapping from fuzzy concepts of condition parts to the fuzzy concepts of conclusion parts. Conventionally, vectors are used to define fuzzy concepts and matrices are used to define a fuzzy mapping between fuzzy conditions and conclusions. This approach, however, does not satisfy the existing condition property, i.e., when a fuzzy input data exactly matches to a fuzzy condition, fuzzy output data should be mapped to a corresponding fuzzy conclusion. Alternatively, we propose a parameterized approach in which every fuzzy concept is described by a parameterized standard function, including fuzzy conditions and fuzzy conclusions. A fuzzy IF-THEN-ELSE rule takes the parameterized fuzzy concept as an input, and produces a standard function with new parameters as an output. New parameters are determined by a parameterwise interpolation. That is, each output parameters are determined by interpolating parameters of the same class contained in fuzzy conclusions. Obviously, the proposed scheme always satisfies the existing condition property.