• Journal of Surface Science and Engineering
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• v.53 no.3
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• pp.95-103
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• 2020

In this study, the material used in the hot dip galvanizing equipment was poorly corrosion-resistant, so it was performed to solve the cost and time problems caused by equipment replacement. The theoretical calculation was performed using the DV-Xα method(Discrete Variational Local-density approximation method). The alloy (STS4XX series) of the equipment currently used has a martensite phase. Therefore, the theoretical calculation was performed by applying P4 / mmm, which is a tetragonal structure. The new alloy was chosen by designing theoretical values close to existing materials. Considering elements that contribute to corrosion, most have high prices. Therefore, the design was completed by adjusting the content using only the components of the reference material in the theoretical design. The final design alloys were chosen as D6 and D9. Designed D6 and D9 were dissolved and prepared using an induction furnace. After the heat treatment process was completed, the corrosion rate of the alloys was confirmed by using the potentiodynamic polarization test. The surface of the prepared alloys were processed horizontally and then polished to # 1200 using sand paper to perform potentiodynamic polarization test. Domestic products: 4.735 mpy (mils / year), D6: 0.9166 mpy, D9: 0.3372 mpy, alloys designed than domestic products had a lower corrosion rate. Therefore, the designed alloy was expected to have better erosion resistance.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.667-676
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• 2002

Digital environment that is represented to Internet is displacing business way of industry and business achievement way with the fast speed being giving great change on life whole. Improve existent business process utilizing Internet and Web connection technology, information superhighway to tradition industrialist manufacturer and e-Transformation's propulsion that wish to maximize productivity and administration efficiency is spread vigorously. In this paper, administration efficiency raising of Web-based factory monitoring system to do monitoring when everywhere integrating operation present condition current point of time of discrete factories in inside and outside of the country by purpose design and implemented. That is, do to normalize system structure and achievement function, and administration data of Web-based, and design using VML (Unified Modeling Language) and take advantage of ASP (Active Server Pages) and implemented web function. Implemented Web-based factory monitoring system is applying two factory (Kl, K2) of K CO., LTD. tire operation division to caravan, and application result was evaluated by very efficient thing to grasp operation situation of whole factory synthetically.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.915-927
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• 2008

Networked control systems(NCSs) have gained increasing attention in recent years due to their advantages and potential applications. The network Quality-of-Service(QoS) in NCSs always fluctuates due to changes of the traffic load and available network resources. To handle the network QoS variations problem, this paper presents an intelligent scheduling control method for NCSs, where the sampling period and the control parameters are simultaneously scheduled to compensate the effect of QoS variation on NCSs performance. For NCSs with network-induced delays and packet dropouts, a discrete-time switch model is proposed. By defining a sampling-period-dependent Lyapunov function and a common quadratic Lyapunov function, the stability conditions are derived for NCSs in terms of linear matrix inequalities(LMIs). Based on the obtained stability conditions, the corresponding controller design problem is solved and the performance optimization problem is also investigated. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.390-397
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• 2013

This paper presents a consensus algorithm for uMAS (uncertain Multi-Agent Systems). Unlike previous results in which only nominal models for agents are considered, it is assumed that the uncertain agent model belongs to a known polytope set. In the middle of deriving the proposed algorithm, a convex set is found which includes all uncertainties in the problem using convexity of the polytope set. This set plays an important role in designing the consensus algorithm for uMAS. Based on the set, a consensus condition for uMAS is proposed and the corresponding consensus design problem is solved using LMI (Linear Matrix Inequality). Simulation result shows that the proposed consensus algorithm successfully leads to consensus of the state of uMAS.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.2
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• pp.80-86
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• 2011

This paper presents an integrated variable amplitude high voltage pulse generation circuit with low power and small size for driving industrial piezoelectric printer heads. To solve the problems of large size and power overhead of conventional pulse generators that usually assembled with multiple high-cost discrete ICs on a PCB board, we have designed a new integrated circuit (IC) chip. Since all the functions are integrated on to a single-chip it can achieve low cost and control the high-voltage output pulse with variable amplitudes as well. It can also digitally control the rising and falling times of an output high voltage pulse by using programmable RC time control of the output buffer. The proposed circuit has been designed and simulatedd in a 180[nm] Bipolar-CMOS-DMOS (BCD) technology using HSPICE and Cadence Virtuoso Tools. The proposed single-chip pulse generation circuit is suitable for use in industrial printer heads requiring a variable high voltage driving capability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.619-625
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• 2000

A many control techniques have been proposed in order to improve the control performance of the discrete-time domain control system. In the position control system, the output of a controller is generally used as the input of a plant but the undesired noise is included in the output of a controller. Therefore there is a need to used a precompensator for rejecting the undesired noise. In this paper, The expanded I-PD control system with a precompensator is constructed. The precompensator and I-PD controller are designed by a neural network and these coefficients are changed automatically to be a desired response of system when the response characteristic of system is changed under a condition.

• Journal of Biosystems Engineering
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• v.21 no.3
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• pp.283-292
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• 1996

Automatic guidance of farm tractors would improve productivity by reducing operator fatigue and increasing machine performance. To control tractors within $\pm$5cm of the desired path, fuzzy and adaptive steering controllers were developed to evaluate their characteristics and performance. Two input variables were position and yaw errors, and a steering command was fed to tractor model as controller output. Trapezoidal membership functions were used in the fuzzy controller, and a minimum-variance adaptive controller was implemented into the 2-DOF discrete-time input-output model. For unit-step and composite paths, a dynamic tractor simulator was used to test the controllers developed. The results showed that both controllers could control the tractor within $\pm$5cm error from the defined path and the position error of tractor by fuzzy controller was the bigger of the two. Through simulations, the output of self-tuning adaptive controller was relatively smooth, but the fuzzy controller was very sensitive by the change of gain and the shape of membership functions. Contrarily, modeling procedure of the fuzzy controller was simple, but the adaptive controller had very complex procedure of design and showed that control performance was affected greatly by the order of its model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.11
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• pp.1311-1318
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• 2012

Vehicle systems are frequently exposed to parameter uncertainties such as vehicle speed and height of center of gravity. If a controller is designed to be robust against these parameter uncertainties, the rollover prevention capability can be considerably enhanced. In this study, robust controllers $H_2$ and $H_{\infty}$ are designed by using LMI for vehicle rollover prevention control in the discrete time domain. Some simulations using CarSim, a reliable simulation tool, are performed to validate the proposed controllers.