• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.960-967
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• 2008

This paper shows that design of a robustly stable repetitive control system is equivalent to that of a feedback control system for an uncertain linear time-invariant system satisfying the well-known robust performance condition. Once a feedback controller is designed to satisfy the robust performance condition, the feedback controller and the repetitive controller using the performance weighting function robustly stabilizes the repetitive control system. It is also shown that we can obtain a steady-state tracking error described in a simple form without time-delay element if the robust stability condition is satisfied for the repetitive control system. Moreover, using this result, a sufficient condition is provided, which ensures that the least upper bound of the steady-state tracking error generated by the repetitive control system is less than or equal to the least upper bound of the steady-state tracking error only by the feedback system.

• Journal of the Korea Institute of Building Construction
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• v.2 no.2
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• pp.151-156
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• 2002

When fresh concrete is exposed to low temperature, the concrete may suffer frost damage due to freezing at early ages and strength development may be delayed. One of the solution methods for resolve these problems is to reduce freezing temperature of concrete by the use of chemical admixture called Accelerators for freezing resistance. In this study, we investigate the effect on strength development of cement mortar using accelerators for freezing resistance with the variance curing condition. As the result of this study, the mortar using accelerators for freezing resistance show that continuously strength development in curing condition of -5$^{\circ}C$. And compressive strength under the variance temperature condition was higher than constant temperature condition in same maturity.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.3-8
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• 2004

When most manufacturing company produce grinding product operators decide grinding condition by experience and subjective judgment. The study on grinding manufacture have been developed to get the grinding condition with the same result when non-experienced or experienced worker work. The objective of this study is to develope the grinding condition and predict the result of grinding by neural network. Several discussions were made in following areas as; getting MRR with image processing, the architecture optimization of neural network with experiment design, analysis of the input neurons using sensitivity approach. The results showed that the developed approach was the best method in predicting grinding condition with respect to surface finish quality.

• Water Engineering Research
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• v.5 no.1
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• pp.1-16
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• 2004

The purpose of this study is to understand the characteristics of hourly PET(Potential Evapo Transpiration) variation estimated using Penman ET model. The estimated PET using Penman model was compared with measured ET. For this study, two subwatersheds were selected, and fluxes, meteorological data and soil moisture data were measured during the summer and winter days. During the winter days, the aerodynamic term of Penman ET is much greater than that of energy term of Penman ET for dry soil condition. The opposite phenomena appeared fer wet soil condition. During the summer days, energy term is much more important factor for ET estimation compared with aerodynamic term regardless of soil moisture condition. Penman ET, measured ET, and energy term show the similar hourly variation pattern mainly because the influence of net radiation on the estimation of Penman ET is much more significant compared with other variables. Even though there are much more soil moisture in the soil during the wet days, the estimated hourly ET from Penman model and measured hourly ET have smaller values compared with those of dry days, indicating the effect of cloudy weather condition.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.263-272
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• 2000

In this paper we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastcic approximation method it is regarded as a stochastic recursive filter algorithm. In addition we provide a filtering and control condition for a stochastic nonlinear system called the perfect filtering condition in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable and the proposed neural controller is more efficient than the conventional LQG controller and the canonical LQ-Neural controller.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.4
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• pp.37-43
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• 2008

Working condition is one of the most important factors in precision working. In this study, we optimized the vibration acceleration level(VAL) of Al 2024 alloy to select optimum working condition of side wall end-milling using RSM(Response Surface Methodology). RSM was well adapted to make analytic model for minimizing vibration acceleration, created the objective function and saved a great deal of computational time. Therefore, it is expected that the proposed optimization procedure using RSM can be easily utilized to solve the optimization problem of working condition. The experimental results of the surface roughness and VAL showed the validity of the proposed working condition of side wall end-milling as it can be observed.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.5
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• pp.526-529
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• 2004

The nematic liquid crysta](NLC) aligning capabilities using a-C:H thin film deposited at the three kinds of rf bias condition were investigated. A high pretilt angle of NLC on low substrate rf bias applied a-C:H thin films was observed and the low pretilt angle of the NLC on high substrate rf bias applied a-C:H thin films was observed. Consequently, the high NLC pretilt angle and the good aligning capabilities of LC alignment by the IB alignment method on the a-C:H thin film deposited at 1 W rf bias condition can be achieved. It is considered that pretilt angle of the NLC may be attributed to substrate rf bias condition and IB energy time. Therefore, LC alignment is affected by topographical structure forming strong IB energy.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.6
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• pp.127-132
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• 2000

Morphological analysis of wear particles is one of useful methods for machine condition monitoring because it is well reflected in machine driving state. This paper was undertaken to apply to the condition monitoring of hydraulic piston motor. The lubricating wear test was performed under different experimental conditions using the wear test device and wear specimens of the pin on disk type was rubbed in paraffinic base oil by three kinds of lubricating materials, varying applied load, sliding distance. The four shape parameters(50% volumetric diameter, aspect, roundness and reflectivity) are used for morphological analysis of wear particles. The results showed that the four shape parameters of wear particles depend on a kind of the lubricating materials. It was capable of calculating presumed wear volume for three kinds of materials on driving time to foresee as damage condition of lubricating materials.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.346-352
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• 1998

In this paper, we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastic approximation method, it is regarded as a stochastic recursive filter algorithm. In addition, we provide a filtering and control condition for a stochastic nonlinear system, called perfect filtering condition, in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence, the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable. and the proposed neural controller is more efficient than the conventional LQG controller and the canoni al LQ-Neural controller.

• 연구논문집
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• s.22
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• pp.65-74
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• 1992

This paper aims at calculating optimum design dimensions to minimize the weight satisfied strain and stress intensity of the frame while loading maximum weight into a mechanical press in the static condition. Analysis of the frame was carried out by using the FEM, then the optimum condition was obtained by using these data. As modeling in the finite element analysis has great impact on the reliablity of analysis results, the analyzed object was selected a 150-ton mechanical press of J Company, the part little affected to structural rigidity was simplified, the load condition was considered in the only maximum load, the boundary condition was used by giving symmetric displacement due to symmetric boundary condition, the finite element was applied a linear membrane element. An intermediate processor program applied the normal ANSYS to analyze finite elements was developed, and the design sensitivity was calculated. This program was applied to the optimum design.