• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.377-377
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• 2000

Current software cost estimation models, such as the 1951 COCOMO, its 1987 Ada COCOMO update, is composed of nonlinear models, such as product attributes, computer attributes, personnel attributes, project attributes, effort-multiplier cost drivers, and have been experiencing increasing difficulties in estimating the costs of software developed to new lift cycle processes and capabilities. The COCOMO II is developed fur new forms against the current software cost estimation models. This paper provides a case-based analysis result of the cost driver in the software cost models, such as COCOMO and COCOMO 2.0 by fuzzy and neural network.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.102.3-102
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• 2001

In this paper, we propose a novel method that can detect face region effectively with fuzzy theory and neural network We make fuzzy rules and membership functions to describe the face color. In this algorithm, we use a perceptually uniform color space to increase the accuracy and stableness of the nonlinear color information. We use this model to extract the face candidate, and then scan it with the pre-built sliding window by using a neural network-based pattern-matching method to find eye. A neural network examines small windows of face candidate, and decides whether each window contains eye. We can standardize the face candidate geometrically with detected eyes.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.245-247
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• 1999

The problem of small-signal stability is usually one of insufficient damping of system oscillations. The use of power system stabilizers to control generator excitation system os the most cost effective method of enhancing the small-signal stability of power system. This paper presents the fuzzy type stabilizing controller to damp out the sustained oscillation, which is observed in normal operation. through the comparative simulation with PI type power stabilizer under various system operating condition, the efficiency of fuzzy stabilizing controller with respect to nonlinear power system is verified.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.553-558
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• 1994

In this paper, we present a new approach for the automation of deburring process. An algorithm for teaching skills of a human expert to a robot manipulator is developed. This approach makes use of TSK fuzzy model that can express a highly nonlinear functional relation with small number of rules. Burr features such as height, width, area, cutting area are extracted from image processing by use of the vision system. Cutting depth, repeative number and normal cutting force are chosen as control signals representing actions of the human expert. It is verified that our processed fuzzy model can accurately express the skills of human experts for the deburring process.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1276-1281
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• 2006

In general, the wheel-skid prevention of braking system is very important in modern railway applications. This is because wheel-skid can lead to an increase in noise and vibration from wheels with flat points, as well as an increased braking distance. However conventional anti-skid control has problems because wheel adhension and skid characteristics are very difficult nonlinear systems and time consuming to accurately model. In this paper, we design a fuzzy controller using a model of relation between ahdension and braking force, we show that anti-skid fuzzy controller has a very good performance, performing better than the previous conventional controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.496-508
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• 1999

Fuzzy System which are based on membership functions and rules can control nonlinear uncertain complex systems well. However Fuzzy logic controller(FLC) has problems; It is difficult to design the stable FLC and FLC depends mainly on individual experience. Although FLC can be designed using the error back-propagation algorithm it takes long time to converge into global optimal parameters. Well-developed linear system theory should not be replaced by FLC but instead it should be suitably used with FLC. A new methodology is introduced for designing THEN-PART membership functions of FLC based on its well-tuned state feedback controller. A example of inverted pendulum is given for demonstration of the robustness of proposed methodology.

• Journal of Power Electronics
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• v.14 no.3
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• pp.598-607
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• 2014

This paper proposes a frequency-locked loop (FLL) scheme for a single-phase grid-connected converter. A second-order generalized integrator (SOGI) based on fuzzy logic (FL) is applied to this converter to achieve precise phase angle detection. The use of this method enables the compensation of the nonlinear characteristic of the frequency error, which is defined in the SOGI scheme as the variation of the central frequency through the self-tuning gain. With the proposed scheme, the performance of the SOGI-FLL is further improved at the grid disturbances, which results in the stable operation of the grid converter under grid voltage sags or frequency variation. The PSIM simulation and experimental results are shown to verify the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.344-346
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• 1995

In this paper a drive strategy of AC Servo Motor using Fuzzy method was proposed. Since the transfer function of the plant is nonlinear and very complicated, there are difficultly in driving the system with real time. The performance of out method is confirmed by computer simulation and experimental results. The high performance and high accuracy of the driving system. Fuzzy is designed and proposed.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.3
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• pp.102-109
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• 1996

In this paper, we present a new approach for the automation of deburring process. An algorithm for teaching skills of a human expert to a robot manipulator is developed. This approach makes use of TSK fuzzy mode that can wxpress a highly nonlinear functional relation with small number of rules. Burr features such as height, width, area, grinding area are extracted from image processing by use of the vision system. Grinding depth, repetitive number and normal grinding force are chosen as control signals representing actions of the human expert. It is verified that our proposed fuzzy model can accurately express the skills of human experts for the deburring process.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.441-447
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• 2012

This paper presents a design technique of a Takagi-Sugeno (T-S) fuzzy-model-based $H_{\infty}$ controller for autonomous underwater vehicles (AUVs). The design procedure aims to render the stabilizing controller which satisfies performance of the diving control for AUVs in the presence of the disturbance. A nonlinear AUV is modeled by the T-S fuzzy system through the sector nonlinearity. By using Lyapunov function, the sufficient conditions are derived to guarantee the performance of robust depth control in the format of linear matrix inequality (LMI). To succeed for diving control of AUV, we add the constraints on the diving and pitch angles in the LMI conditions. Through the simulation, we confirm the effectiveness of the proposed methodology.