• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1998년도 하계학술대회 논문집 B
• /
• pp.537-540
• /
• 1998

This thesis deals with the design problem of the state estimator for digital servo system. Digital servo system has input time delay, which depends on the size of control algorithm. The delayed input is a factor that brings out the state estimation error. So, in order to reduce this state estimation error of the system, we proposes a state estimator in which the delayed input of the system is considered. At first, a discrete-time state-space model is established accounting for the delayed input. Next, the state estimator is designed based on this model. we employ Kalman filter algorithm in design of the state estimator. The performance of proposed state estimator is exemplified via some simulations and experiment for servo system. And robustness of the proposed estimator to modelling error by variation of the system parameter is also shown in these simulations.

• 융합경영연구
• /
• 제11권1호
• /
• pp.31-44
• /
• 2023

Purpose: This study aims to figure out the characteristics of corporate life cycle and resource input in terms of the sustainability diagnosis of pharmaceutical companies in Korea. Research design, data, and methodology: Using the Gompertz model under the assumption that companies have finite resources, this study tries quantitative interpretation of life cycle and resource input pattern for longevity companies with 25 years of experience among 158 pharmaceutical companies listed on Korean stock market based on maturity of revenue. Results: The study found revenue maturity through Gompertz model was statistically correlated with enterprise value. According to the life cycle analysis, more than 95% of 59 pharmaceutical companies were in the growth and maturity phase and have an average life cycle of 88 years and an average remaining life of 52 years. Regarding maturity profile of resource input, maturity of employees was generally high more than 60% and this meant there was jobless growth in Korean pharmaceutical industry. Conclusion: This study demonstrated there is a high statistical correlation between the maturity of a company's resource input and its revenue and enterprise value. It is believed that these results could be utilized as a basis for high fidelity function that predict revenue and enterprise value based on resource input information.

• Journal of Electrical Engineering and information Science
• /
• 제2권4호
• /
• pp.53-58
• /
• 1997

In this paper, the power system stabilizer(PSS) using the sliding mode observer-model following(SMO-MF) with closed-loop feedback (CLF) for single machine system is extended to multimachine system. This a multimachine SMO-MF PSS for unmeasureable plant state variable is obtained by combining the sliding mode-model following(SM-MF) including closed-loop feedback(CLF) with the full-order observer(FOO). And the estimated control input for unmeasurable plant sate variables is derived by Lyapunov's second method to determine a control input that keeps the system stable. Time domain simulation results for the torque angle and for the angular velocity show that the proposed multimachine SMO-MF PSS including CLF for unmeasurable plant sate variables is able to damp out the low frequency oscillation and to achieve asymptotic tracking error between the reference model state at different initial conditions and at step input.

• 한국대기환경학회지
• /
• 제5권1호
• /
• pp.1-10
• /
• 1989

The sensitivity analysis is a method to quantify to what extent the output of a model changes with the values of input parameters. This will lead to increase model accuracy through measurement validation. Three line source air quality models, HIWAY 2, PAL, and CALINE 3 were selected for this study. The input parameters analysed included wind speed, wind direction, stability, emission rate, mixing height, receptor distance, initial dispersion coefficient, surface roughness, and averaging time. It turned out that PAL model generally showed higher concentration than other two models, and that between CALINE 3 and HIWAY 2, CALINE 3 showed higher concentration than HIWAY 2 model near the line sources, but beyond a certain downwind distances HIWAY 2 model showed higher concentration. The modesl were very sensitive to wind speed especially in the range of 0 $\sim$ 1 m/s and to wind direction near the parallel wind to streets. In case of emission rate, the output concentration was directly proportional to these input parameters. And the sensitivity of the input parameters such as stability, mixing height, initial dispersion coefficient, surface roughness, and averaging time were not very significant.

• JSTS:Journal of Semiconductor Technology and Science
• /
• 제10권4호
• /
• pp.300-308
• /
• 2010

This paper describes the development of a low-power electrocardiogram (ECG) touch sensor intended for the use with two dry metal electrodes. An equivalent ECG extraction circuit model encountered in a ground-free two-electrode configuration is investigated for an optimal sensor read-out circuit design criteria. From the equivalent circuit model, (1) maximum sensor resolution is derived based on the electrode's background thermal noise, which originates from high electrode-skin contact impedance, together with the input referred noise of instrumentation amplifier (IA), (2) 60 Hz electrostatic coupling from mains and motion artifact are also considered to determine minimum requirement of common mode rejection ratio (CMRR) and input impedance of IA. A dedicated ECG read-out front end incorporating chopping scheme is introduced to provide an input referred circuit noise of 1.3 ${\mu}V_{rms}$ over 0.5 Hz ~ 200 Hz, CMRR of IA > 100 dB, sensor resolution of 7 bits, and dissipating only 36 ${\mu}W$. Together with 8 bits synchronous successive approximation register (SAR) ADC, the sensor IC chip is implemented in 0.18 ${\mu}m$ CMOS technology and integrated on a 5 cm $\times$ 8 cm PCB with two copper patterned electrodes. With the help of proposed touch sensor, ECG signal containing QRS complex and P, T waves are successfully extracted by simply touching the electrodes with two thumbs.

• 한국환경과학회지
• /
• 제24권7호
• /
• pp.865-874
• /
• 2015

This study was conducted to investigate the correlation between the distribution chart and input data of the predicted 3-second gust and damage cost, by using the forecast field and analysis field of Regional Data Assimilation Prediction System (RDAPS) as initial input data of Korea risk assessment model (RAM) developed in the preceding study. In this study the cases of typhoon Rusa which caused occurred great damage to the Korean peninsula was analyzed to assess the suitability of initial input data. As a result, this study has found out that the distribution chart from the forecast field and analysis field predicted from the point where the effect due to the typhoon began had similarity in both 3-second gust and damage cost with the course of time. As a result of examining the correlation, the 3-second gust had over 0.8, and it means that the forecast field and analysis field show similar results. This study has shown that utilizing the forecast field as initial input data of Korea RAM could suit the purpose of pre-disaster prevention.

• 대한전기학회논문지
• /
• 제38권2호
• /
• pp.137-143
• /
• 1989

System modeling from input-output data is generally carried out in two steps. The first step is to determine the form of the model. In the second step, the parameters of the model in an appropriate form are estimated from input-output data. This paper presents a method, via single term Walsh functions, for simultaneous estimation of the order and the parameters of linear systems from input-output data. The estimation of the model order is based on minimizing an error function, which is defined by Desai and Fairman. Unknown system parameters are recursively estimated by the least square method.

• Journal of the Korean Statistical Society
• /
• 제5권1호
• /
• pp.35-48
• /
• 1976

Since the solution vector for input-output forecasting models is not directly obtainable, several iterative procedures have been proposed and utilized. As is often the case in numerical analysis, the question of the consistency between the original system and the converged system of the proposed iteration has been ignored, and no one has tried to express the converged solution explicitly. This paper examines this question and points out the inconsistencies between various well-known iterative procedures used to solve input-output models and the original input-output system.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
• /
• pp.2885-2887
• /
• 2005

We introduce a hybrid identification of information granulation(IG)-based fuzzy model to carry out the model identification of complex and nonlinear systems. To optimally design the IG-based fuzzy model we exploit a hybrid identification through genetic alrogithms(GAs) and Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the seleced input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of HCM clustering help determine the initial paramters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the inital parameters are tuned effectively with the aid of the GAs and the least square method. Numerical example is included to evaluate the performance of the proposed model.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.9-11
• /
• 2005

We propose a optimal identification of information granulation(IG)-based fuzzy model to carry out the model identification of complex and nonlinear systems. To optimally identity we use genetic algorithm (GAs) sand Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the selected input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method. Numerical example is included to evaluate the performance of the proposed model.