• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.469-471
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• 1999

In this paper, the method of Space-Vector Pulse Width Modulation(SVPWM) with Fuzzy Logic Regulator(FLR) is proposed. In a conventional SVPWM, the procedures of phase transformation and choosing PWM patterns are complex. So, it should be implemented with high performance processor like Digital Signal Processor(DSP). In order to reduce a calculation burden, a proposed system adopts FLR. Using a linguistic contro strategy based on expert knowledge, FLR relieves the processor from a heavy computations. In simulations, the proposed system is validated.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.192-195
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• 2008

People have tendency of forgetting music title, though they easily remember particular part of music. If a music search system can find the title through a part of melody, this will provide very convenient interface to users. In this paper, we propose an algorithm that enables this type of search using feature transformation function. The original music is transformed to new feature information with sequential melodies. When a melody that is a part of search music is given to the system, the music retrieval system searches the music similar to the feature information of the melody. Moreover, this transformation function can be easily extended to various music recognition systems.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.313-320
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• 1999

In this paper, a translation, rotation and scale invariant system for the classification of closed 2D images using the bispectrum of a contour sequence and the weighted fuzzy mean method is derived and compared with the classification process using one of the competitive neural algorithm, called a LVQ(Learning Vector Quantization). The bispectrun based on third order cumulants is applied to the contour sequences of the images to extract fifteen feature vectors for each planar image. These bispectral feature vectors, which are invariant to shape translation, rotation and scale transformation, can be used to represent two-dimensional planar images and are fed into an classifier using weighted fuzzy mean method. The experimental processes with eight different shapes of aircraft images are presented to illustrate the high performance of the proposed classifier.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1371-1376
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• 1990

The paper presents a method of constructing simple fuzzy control rules for the determination of stabilizing signals of automatic voltage regulator and governor, which are controllers of electric power systems. Fuzzy control rules are simplified by considering a coordinate transformation with the rotation angle .theta. on the phase plane, and by expanding the range of membership functions. Also, two rotation angles .theta. $_{1}$ and .theta. $_{2}$ are selected for the linearizable region and the nonlinear one of the system, respectively. Here, .theta. $_{1}$ is chosen by the pole assignment method, and .theta. $_{2}$ by a performance index. Fuzzy inference is applied to the connection of two rotation angles .theta. $_{1}$ and .theta. $_{1}$ by regarding the distance from the desired equilibrium point as a variable of condition parts. The control effect is demonstrated by an application of the proposed method to one-machine infinite-bus power system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.103-106
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• 2003

선박의 초기 설계 단계에서는 작업의 용이성과 설계자의 관습 둥으로 인해 선박모델은 통상 2차원 모델로서 표현된다. 하지만 제품의 상세 설계 단계로 넘어가면 부품의 가공정보 도출, 부품간의 간섭확인, 제품의 성능해석의 용이성 등의 이유로 인해 제품 정보는 3차원 디지털 모델로서 표현되어야 한다. 그러나 현재까지 이러한 과정은 설계자에 의해 수작업으로 진행되고 있고 이 과정에서 공기의 지연, 설계자에 의한 해석 및 입력 오류 둥 많은 문제점이 야기되고 있다. 본 연구에서는 이러한 문제의 해결을 위해, Fuzzy 추론 기법을 이용한 2차원 선박 모델의 3차원 디지털 모델로의 자동 변환 기술을 검토한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.228-233
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• 1997

An efficient corner matching algorithm is developed to minimize the amount of calculation. To reduce the amount of calculation, all available information from a corner detector is used to make model. This information has uncertainties due to discretization noise and geometric distortion, and this is represented by fuzzy rule base which can represent and handle the uncertainties. Form fuzzy inference procedure, a matched segment list is extracted, and resulted segment list is used to calculate the transformation between object of model and scene. To reduce the false hypotheses, a vote and re-vote method is developed. Also an auto tuning scheme of the fuzzy rule base is developed to find out the uncertainties of features from recognized results automatically. To show the effectiveness of the developed algorithm, experiments are conducted for images of real electronic components.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.86-89
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• 2000

In this paper, we consider a fuzzy system representation for polynomials of two variables. The representation we use is an exact transformation of the corresponding cubic spline interpolation function. We examine some of the properties of their fuzzy rule tables md prove that the rule table is symmetric or antisymmetric depending on whether the polynomial is symmetric or antisymmetric. A few examples are included to verify our proof. These results not only provide some insights on properties of the cubic spline interpolation coefficients but also provide some help in setting up fuzzy rule tables for functions of two variables.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1211-1214
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• 1993

In this paper, we present a fuzzy-number-oriented methodology to model uncertain geometric robot environment and to manipulate geometric uncertainty between robot coordinate frames. We describe any geometric primitive of robot environment as a parameter vector in parameter space. Not only ill-known values of the parameterized geometric primitive but the uncertain quantities of coordinate transformation are represented by means of fuzzy numbers restricted to appropriate membership functions. For consistent interpretation about geometric primitives between different coordinate frames, we manipulate these uncertain quantities using fuzzy arithmetic.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.491-501
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• 2002

Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.27-32
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• 2002

This paper describes a fuzzy steering controller for an outdoor autonomous mobile robot using MR(magneto-resistive) sensor. Using the magnetic field difference values(dBy, dBz) obtained from the MR sensor, we designed fuzzy logic controller for driving the robot on the road center and proposed a method to eliminate the Earth magnetic field. To develop an autonomous mobile robot simulation program, we have done modeling MR sensor, mobile robot and coordinate transformation. A computer simulation of the robot including mobile robot dynamics and steering was used to verify the driving performance of the mobile robot controller using the fuzzy logic. So, we confirmed the robustness of the proposed fuzzy controller by computer simulation.