• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.109-113
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• 2002

In this paper, we propose a new intrusion detection algorithm based on clustering: Kernel-ART, which is composed of the on-line clustering algorithm, ART (adaptive resonance theory), combining with mercer-kernel and concept vector. Kernel-ART is not only satisfying all desirable characteristics in the context of clustering-based 105 but also alleviating drawbacks associated with the supervised learning IDS. It is able to detect various types of intrusions in real-time by means of generating clusters incrementally.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.46-54
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• 1998

This paper presents a method for designing robust fuzzy $H^{\infty}$ controllers which stabilize nonlinear systems with parameter uncertainty adn guarantee an induced $L_{2}$ norm bound constraint on disturbance attenuation for all admissible uncertainties. Takagi and Sugeno's fuzzy models with uncertainty are used as the model for the uncertain nonlinear systems. Fuzzy control systems utilize the concept of so-called parallel distributed compensation(PDC). Using a single quadratic Lyapunov function, the stability condition satisfying decay rate and disturbance attenuation condition for Takagi and Sugeno's fuzzy model with parameter uncertainty are discussed. A sufficient condition for the existence of robust fuzzy $H^{\infty}$ controllers is then presented in terms of linear matrix inequalities(LMIs). Finally, design examples of robust fuzzy $H^{\infty}$ controllers for uncertain nonlinear systems are presented.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.60-63
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• 2004

An innovative in-core neutron flux mapping system has been developed and applied successfully for service in a commercial pressurized water reactor. With the benefit of double indexing path selector (Dip $s^{ⓡ}$) mechanism, the reliability of the detector drive system has been improved five times higher than that of conventional systems, and the problems caused by the serious friction generated between the detector cable and guide tubing has been solved completely because the Dip $s^{ⓡ}$ architecture allows the detector guide tubings to have larger curvature and shorter length in nature. The simple and fast maintenance is particularly emphasized in the detector drive system to secure minimum radiation exposure to the maintenance personnel by optimizing the number of components and providing easy access to the components. The programmable logic controller based digital controller with Window $s^{ⓡ}$ based operator s console provides fully automated and user friendly operation and maintenance support means.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.396-399
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• 1995

This paper presents a new formulation of the kinematics of closed-chain mechanisms and its applications to obtaining the kinematic solutions and analyzing the singularities. Closed-chain mechanisms under consideration may have the redundancy in the number of joints. A closed-chain mechanism can be treated as the parallel connection of two open-chains with respect to a point of interest. The kinematics of a closed-chain mechanism is then obtained by imposing the kinematic constraints of the closed-chain on the kinematics of the two open-chains. First, we formulate the kinematics of a closed-chain mechanism using the kinematic constraint between the controllable active joints and the rest of joints, instead of the kinematic constraint between the two open-chains. The kinematic formulation presented in this paper is valid for closed-chain mechanisms with and without the redundancy. Next, based on the derived kinematics of a closed-chain mechanism, we provide the kinematic solutions which are more physically meaningful and less sensitive to numerical instability, and also suggest an effective way to analyze the singularities. Finally, the computational cost associated with the kinematic formulation is analyzed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.427-432
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• 2005

This paper is concerned with a simultaneous design of TSK (Takagi-Sugeno-Kang)-linguistic fuzzy models with uncertain model output and the computationally efficient representation. For this purpose, we use the fundamental idea of linguistic models introduced by Pedrycz and develop their comprehensive design framework. The design process consists of several main phases such as (a) the automatic generation of the linguistic contexts by probabilistic distribution using CDF (conditional density function) and PDF (probability density function) (b) performing context-based fuzzy clustering preserving homogeneity based on the concept of fuzzy granulation (c) augment of bias term to compensate bias error (d) combination of TSK and linguistic context in the consequent part. Finally, we contrast the performance of the enhanced models with other fuzzy models for automobile MPG predication data and coagulant dosing process in a water purification plant.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1510-1515
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• 2005

This paper is concerned with a Logic-based Fuzzy Neural Networks (LFNN) with the aid of fuzzy granulation. As the underlying design tool guiding the development of the proposed LFNN, we concentrate on the context-based fuzzy clustering which builds information granules in the form of linguistic contexts as well as OR fuzzy neuron which is logic-driven processing unit realizing the composition operations of T-norm and S-norm. The design process comprises several main phases such as (a) defining context fuzzy sets in the output space, (b) completing context-based fuzzy clustering in each context, (c) aggregating OR fuzzy neuron into linguistic models, and (c) optimizing connections linking information granules and fuzzy neurons in the input and output spaces. The experimental examples are tested through two-dimensional nonlinear function. The obtained results reveal that the proposed model yields better performance in comparison with conventional linguistic model and other approaches.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.516-523
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• 2013

This paper investigates an improved stator flux linkage observer for sensorless permanent magnet synchronous motor (PMSM) drives using a voltage-based flux linkage model and an adaptive sliding mode variable structure. We propose a new observer design that employs an improved sliding mode reaching law to achieve better estimation accuracy. The design includes two models and two adaptive estimating laws, and we illustrate that the design is stable using the Popov hyper-stability theory. Simulation and experimental results demonstrate that the proposed estimator accurately calculates the speed, the stator flux linkage, and the resistance while overcoming the shortcomings of traditional estimators.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.1-6
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• 2002

In this study, we propose the new color-based image retrieval technique using the representative colors of images and their ratios to a total image size obtained through color segmentation in HSV color space. Color information of an image is described by reconstructing the color histogram of an image through Gaussian modelling to its representative colors and ratios. And the similarity between two images is measured by histogram intersection. The proposed method is compared with the existing methods by performing retrieval experiments for various 1280 trademark image database.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.189-192
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• 1996

This paper presents a systematic approach to identify a linguistic fuzzy model for a multi-input and single-output complex system. Such a model is composed of fuzzy rules, and its output is inferred by the simplified reasoning. The structure and membership function parameters for a fuzzy model are automatically and simultaneously identified by GA (Genetic Algorithm). After GA search, optimal parameters for the fuzzy model are finely tuned by a gradient method. A numerical example is provided to evaluate the feasibility of the proposed approach. Comparison shows that the suggested approach can produce the linguistic fuzzy model with higher accuracy and a smaller number of rules than the ones achieved previously in other methods.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2759-2764
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• 2003

Humans usually employ more joints than they actually need, and thus they can be categorized as a kinematically redundant system. Therefore, the behavior of the human body can be analyzed by several redundancy resolution algorithms. Different from typical industrial robots that are fixed to the ground, the COG/ZMP condition should be taken into account in the human body motion in order not to fall down. Thus a COG/ZMP stability index is employed as a measure of stability. Kinematic redundancy inherent in the human body can be exploited to satisfy the COG/ZMP condition. Simulation result shows that the COG/ZMP condition can be satisfied by exploiting the null space motion of the kinematically redundant human body model.