• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
• /
• pp.448-451
• /
• 2000

Fuzzy control has been researched for application of industrial processes which have no accurate mathematical model and could not controlled by conventional methods because of a lack of quantitative input-output data. Intelligent control approach based on fuzzy logic could directly reflex human thinking and natural language to controller comparing with conventional methods. In this paper, the tested system is constructed for sending a ball to the goal position using wind from two DC motors in the path. This system contains non-linearity and uncertainty because of the characteristic of aerodynamics inside the path. The system used in this experiment could be hardly modeled by mathematic methods and could not be easily controlled by linear control manners. The controller, in this paper could control the system containing non-linearity and uncertainty because it is designed based on the input-output data and experimental knowledge obtained by trials.

• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1997년도 춘계학술대회
• /
• pp.156-160
• /
• 1997

In this paper, the control scheme is proposed that PI controller parameter used for TAH speed control is adapted by fuzzy logic method using only the motor current waveform. By scheduling PI parameters, minimization of the vibration and the energy consumption and overcoming AoP loads becomes possible. In in vitro tests experimental results show our approach is a good scheme that is adapted to changing afterloads well.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• pp.436-440
• /
• 1992

As an approach to design the intelligent controller, this paper proposes a new FNN(Fuzzy Neural Network) control method using the hybrid combination of fuzzy logic control and neural network. The proposed FNN controller has two important capabilities, namely, adaptation and learning. These functions are performed by the following process. Firstly, identification of the parameters and estimation of the states for the unknown plant are achieved by the MNN(Model Neural Network) which is continuously trained on-line. And secondly, the learning is performed by FNN controller. The error back propagation algorithm is adopted as a learning technique. The effectiveness of the proposed method will be demonstrated by computer simulation of a two d.o.f. robot manipulator.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제7권1호
• /
• pp.71-76
• /
• 2007

This paper deals with implementing a steganography based multi-modal biometric system. For this purpose, we construct a multi-biometrics system based on the face and iris recognition. Here, the feature vector of iris pattern is hidden in the face image. The recognition system is designed by the fuzzy-based Linear Discriminant Analysis(LDA), which is an expanded approach of the LDA method combined by the theory of fuzzy sets. Furthermore, we present a watermarking method that can embed iris information into face images. Finally, we show the advantages of the proposed watermarking scheme by computing the ROC curves and make some comparisons recognition rates of watermarked face images with those of original ones. From various experiments, we found that our proposed scheme could be used for establishing efficient and secure multi-modal biometric systems.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제14권4호
• /
• pp.240-248
• /
• 2014

We present a robust speaker identification algorithm that uses novel features based on soft bag-of-word representation and a simple Naive Bayes classifier. The bag-of-words (BoW) based histogram feature descriptor is typically constructed by summarizing and identifying representative prototypes from low-level spectral features extracted from training data. In this paper, we define a generalization of the standard BoW. In particular, we define three types of BoW that are based on crisp voting, fuzzy memberships, and possibilistic memberships. We analyze our mapping with three common classifiers: Naive Bayes classifier (NB); K-nearest neighbor classifier (KNN); and support vector machines (SVM). The proposed algorithms are evaluated using large datasets that simulate medical crises. We show that the proposed soft bag-of-words feature representation approach achieves a significant improvement when compared to the state-of-art methods.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제6권4호
• /
• pp.314-320
• /
• 2006

Navigation in environments that are densely cluttered with obstacles is still a challenge for Autonomous Ground Vehicles (AGVs), especially when the configuration of obstacles is not known a priori. Reactive local navigation schemes that tightly couple the robot actions to the sensor information have proved to be effective in these environments, and because of the environmental uncertainties, STSF(Space and Time Sensor Fusion)-based fuzzy behavior systems have been proposed. Realization of autonomous behavior in mobile robots, using STSF control based on spatial data fusion, requires formulation of rules which are collectively responsible for necessary levels of intelligence. This collection of rules can be conveniently decomposed and efficiently implemented as a hierarchy of fuzzy-behaviors. This paper describes how this can be done using a behavior-based architecture. The approach is motivated by ethological models which suggest hierarchical organizations of behavior. Experimental results show that the proposed method can smoothly and effectively guide a robot through cluttered environments such as dense forests.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제12권2호
• /
• pp.108-112
• /
• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2001년도 하계학술대회 논문집 D
• /
• pp.2096-2098
• /
• 2001

Fuzzy control has been researched for application of industrial processes which have no accurate mathematical model and could not be controlled by conventional methods because of a lack of quantitative input-output data. Intelligent control approach based on fuzzy logic could directly reflex human thinking and natural language to controller comparing with conventional methods. In this paper, the tested system is constructed for sending a ball to the goal position using wind from two DC motors in the path. This system contains non-linearity and uncertainty because of the characteristic of aerodynamics inside the path. The system used in this experiment could be hardly modeled by mathematic methods and could not be easily controlled by linear control manners. The controller, in this paper could control the system containing non-linearity and uncertainty.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 하계학술대회 논문집 B
• /
• pp.1128-1131
• /
• 2003

This paper proposes a speed control system based on a fuzzy logic approach, integrated with a simple and effective adaptive algorithms. And this paper attempts to provide a thorough comparative insight into the behavior of induction motor drive with PI, direct and improved fuzzy speed controller. A indirect vector controlled induction motor is simulated under varying operating condition. The validity of the comparative results is confirmed by simulation results for induction motor drive system.

• 전자공학회논문지SC
• /
• 제37권1호
• /
• pp.10-18
• /
• 2000

본 논문에서는 2축 서보시스템에 적용하기 위한 새로운 윤곽 모델링을 이용하여 퍼지논리형 상호결합제어기를 제안한다. 일반적인 각 축 독립제어기는 각 축의 동적 변수와 루프 이득의 불일치로 인해 윤곽 성능을 감소시킨다. 실제적으로 이러한 시스템은 많은 불확실성도 보유하고 있다. 상호결합제어기는 정확한 윤곽을 구하기 위해 모든 축의 위치 오차 정보를 동시에 이용한다. 그러나 일반적인 상호결합제어기는 마찰, 백래쉬 그리고 매개변수 변화를 극복하지 못한다. 또한 정확한 다축 시스템의 수학적 모델을 얻기 힘들기 때문에 서보시스템의 퍼지논리형 상호결합제어기를 제안한다. 이와 더불어 새로운 윤곽 오차 벡터 계산법을 제시한다. 제안한 알고리즘의 성능을 검증하기 위해 실험결과를 나타낸다.