• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1063-1068
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• 2008

A lens system of a camera module for mobile phones is comprised of the composition and design of various shapes of lens. To improve responses such as the modular transfer function (MTF), a lens system should always be constructed by considering uncertainty that can be caused by manufacturing and assembly error. In this study, tolerance optimization using the Latin Hypercube Sampling (LHS) technique is performed. In order to reduce the computational burden of the tolerance optimization process and decrease the influence from numerical noise effectively, we use the Progressive Quadratic Response Surface Modeling (PQRSM), which is one of Sequential Approximate Optimization (SAO) techniques. Using this method, we achieved optimal tolerance for each lens and obtained reliability for satisfying user‘s requirements. In addition, through the design process the manufacturing and assembly cost of a lens system was reduced.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.175-180
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• 2005

Incorrections between model and plant are parameter, system order uncertainties and modeling error due to disturbance like friction. Therefore to achieve a good tracking performance, adaptive discrete time sliding mode tracking controller is used under time-varying desired position. Based on the diophantine equation, a new discrete time sliding function is defined and utilized for the control law. Robustness is increased by using both a recursive least-square method and a sliding function-based nonlinear feedback. The effectiveness of the proposed control algorithm is proved by the results of simulation and experiment.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.819-821
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• 1998

This paper deals with a method or a residual generation for fault isolation in a centrifugal pump with a water circulation system, driven by a speed controlled dc motor. It is based on parity relations derived from the moving-average model of the system and is used to identify sensor faults and two possible brush and impeller faults, where the former is dealt with additive faults, while the latter characterized as discrepancies between the nominal and actual plant parameters of the system is modelled by multiplicative faults. We will represent the propagation of this uncertainty to the model matrices by the approximate handling of partial derivatives of polynomials. With multiplicative faults, the transformation matrix implemented in the residual generator are calculated on-line. The simulation studies demonstrate that small changes of the system can be detected and diagnosed by using the method.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.445-450
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• 1998

In this paper, a robust nonlinear prediction-type controller (RNPC) is developed for the continuous time nonlinear system whose control objective is composed of system output and its desired value. The basic control law of RNPC is derived such that the future response of the system is first predicted by appropriate functional expansions and the control law minimizing the difference between the predicted and desired responses is then calculated. RNPC which involves two controls, i.e., the auxiliary and robust controls into the basic control, shows the stable closed loop dynamics of nonlinear system of any relative degree and provides the robustness to the nonlinear system with parameter/modeling uncertainty. Simulation tests for the position control of a two-link rigid body manipulator confirm the performance improvement and the robustness of RNPC.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.315-322
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• 2004

A direct adaptive state-feedback controller for highly nonlinear systems is proposed. This paper considers uncertain or ill-defined nonaffine nonlinear systems and employs a static fuzzy logic system (FLS). The employed FLS estimates. and adaptively cancels an unknown plant nonlinearity using its proved universal approximation property. A control law and adaptive laws for unknown fuzzy parameters and bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov. The tracking error is guaranteed to be uniformly asymptotically stable rather than uniformly ultimately bounded with the aid of an additional robustifying control term. No a priori knowledge of an upper bound on an lumped uncertainty is required.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1134-1136
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• 1996

A necessary and suficient conditions is proposed for feedback linearizable SISO systems with unknown constant parameters. It is shown that the systems which satisfy the proposed conditions can be transformed into a controllable linear system with unknown parameter and it can be stabilized using the nonlinear feedback linearizing controller. We also present the analysis and implementation of a nonlinear feedback linearizing control for an Electro-Magnetic Suspension (EMS) system. We show that an EMS system is nonlinear feedback linearizable and satisfies the proposed conditions, and hence that the proposed nonlinear feedback controller for an EMS system is robust against mass parameter perturbation and force disturbance.

• Proceedings of the KIEE Conference
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• 2003.07c
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• pp.1632-1634
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• 2003

For lihgtning and switching impulse voltage performances in laboratories, impulse voltage measuring system, which is consisted of voltage divider, recording instrument and connecting system between divider and recording instrument, is used. In order to show reliability of test result in test laboratory, tracebility of these measuring system to be using in test laboratory is needed. In this paper, we describe tracebility and uncertainty of impulse voltage measuring system in test laboratory.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.105-110
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• 2003

Collaborative filtering is one of the methodologies that are most widely used for recommendation system. It is based on a data matrix of each customer's preferences of products. There could be a lot of missing values in such preference. data matrix. This incomplete data is one of the reasons to deteriorate the accuracy of recommendation system. Multiple imputation method imputes m values for each missing value. It overcomes flaws of single imputation approaches through considering the uncertainty of missing values.. The objective of this paper is to suggest multiple imputation-based collaborative filtering approach for recommendation system to improve the accuracy in prediction performance. The experimental works show that the proposed approach provides better performance than the traditional Collaborative filtering approach, especially in case that there are a lot of missing values in dataset used for recommendation system.

• KDI Journal of Economic Policy
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• v.41 no.2
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• pp.1-39
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• 2019

This paper utilizes a life-cycle overlapping-generations model to quantify the welfare effects of plans to postpone the depletion of the National Pension Fund. In order for the model to incorporate the rapidly changing demographic structure of Korea fully, we build and calibrate a model in transition directly. The model is considered suitable for analyzing the effects of demographic changes on the Korean economy and the effects of plans to change the National Pension System. According to a simulation of the model, to postpone the depletion of the National Pension Fund for 30 years, the premium rate must be increased to 18.3% from the current rate of 9%. By postponing the depletion of the fund reserve, young and future generations gain significantly at the expense of the older generations. The simulation results should be, however, interpreted as meaning that the current system is unjustifiably partial to the older generations. Moreover, given the current premium rate, it is desirable to strengthen the income-redistribution function of the National Pension System.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.83-88
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• 2021

Cloud services have become the core infrastructure of the digital economy as a basis for collecting, storing, and processing large amounts of data to trigger artificial intelligence-based services and industrial innovation. Recently, cloud services have been spotlighted as a means of responding to corporate crises and changes in the work environment in a national disaster caused by COVID-19. While the cloud is attracting attention, the speed of adoption and diffusion of cloud services is not being actively carried out due to the lack of trust among users and uncertainty about security, performance, and cost. This study compares and analyzes the "Cloud Service Quality and Performance Management System" and the "Cloud Service Certification System" and suggests complementary points and improvement measures for the cloud service quality and performance management system.