• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.1-8
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• 1997

In order to reject the steady-state tracking error, it is common to introduce integral compensators in servosystems for constant reference signals. However, if the mathematical model of the plant is exact and no disturbance input exists, the integral compensation is not necessary. From this point of view, a two-degree-of-freedom(2DOF) servosystem has been proposed, in which the integral compensation is effective only when there is a modeling error or a disturbance input. The present paper considers robust stability of this 2DOF servosystem incorporating an observer to the structured and unstructured uncertainties of the controlled plant. A robust stability condition is obtained using Riccati inequality, which is written in a linear matrix inequality (LMI) and independent of the gain of the integral compensator. This result impies that if the plant uncertainty is in the allowable set defined by the LMI condition, a high-gain integral compensation can be carried preserving robust stability to accelerate the tracking response.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06a
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• pp.165-170
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• 1998

In this paper, the effect of nonlinear distortion, caused by a high-power amplifier (HPA) in an orthogonal frequency division multiplexing (OFDM) system, on the receiver part is analyzed. Since the HPA, which can be modeled by a memoryless Volterra system, distorts OFDM signals in a nonlinear fashion, the received signal at each subchannel includes the multiplicative distortion of 1-st order as well as additive nonlinear distortion of higher-order. The nonlinear distortion can be viewed as a nonlinear interchannel interference (NICI) since it consists of harmonic distortions and intermodulation distortions, produced by other subchannels affecting the subchannel of interest. In this paper, were analytically derive the variance of NICI in terms of average input power using the Volterra model for HPA, and then calculate the bit-error rate (BER) performance of an OFDM system. Also, we propose a simple method to compensate for the phase distortion in OFDM system amplified by HPA, and calculate its BER performance. Validity of the proposed approach is verified by computer simulations for an OFDM system employing 16-QAM constellation input.

• The Korean Journal of Applied Statistics
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• v.3 no.1
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• pp.89-103
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• 1990

An analysis of mean procedure is presented for testing the significance of two factor interactions for unbalanced case. When at least one factor if at only two levels, the technique is the same as that of Ott(1967) and Nelson(1988) except that we have used the critical value by using the Sidak's multiplicative inequality. The technique can be extended to the case in which both factors more than two levels. Tables of critical values g($\alpha ; (p, q) ; v$) are given for $\alpha$=0.05 and 0.01 ; (p, q) combinations satisfying $3 \leq p \leq q \leq 5$ ; and various degrees of freedom v. We present and prove the formula of the variance of the interactions for the n-way model.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.270-273
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• 2007

In this paper, a SAR-despeck1ing approach of adaptive iteration based a Bayesian model using the lognormal distribution for image intensity and a Gibbs random field (GRF) for image texture is proposed for noise removal of the images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. The iterative approach based on MRF is very effective for the inner areas of regions in the observed scene, but may result in yielding false reconstruction around the boundaries due to using wrong information of adjacent regions with different characteristics. The proposed method suggests an adaptive approach using variable parameters depending on the location of reconstructed area, that is, how near to the boundary. The proximity of boundary is estimated by the statistics based on edge value, standard deviation, entropy, and the 4th moment of intensity distribution.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.144-153
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• 1996

The magnetic levitation system has many advantages, such as little friction, no lubrication, no noise and so on. For this reason, the magnetic levitation system is utilized in the magnetic bearing of high-speed rotor. The method to obtain magnetic force is both the repulsive suspension method and the attraction suspension method need a stabilizing controller because it is a unstable system in natural. This paper presents the design of robust stabilizing servo controller in spite of being the model uncertainties in the magnetic levitation system by $\textit{H}_{\infty}$ control theory using the free parameter. And we investigated the validity of a designed controller through results of the simulation and the actual experiment.

• IE interfaces
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• v.16 no.1
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• pp.16-26
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• 2003

In Korea, cooling power load, which occupies about 20% of peak load in 2000 and fluctuates depending on the popular usage of air conditioning systems, has been recently the focus of the load management. The first work of KEPCO (Korea Electric Power Corporation) to regulate cooling load as low as possible was to estimate its approximate scale and to develop the indirect methods to estimate it from the available time series data for the average hourly loads. However, KEPCO would like to have their methods improved both theoretically and practically. In this paper, we analyze their current indirect methods and detect their faults to design better indirect estimation methods. Under one of the assumptions of "no cooling load in April or May", the linear relationship between basic loads and GDP's, and the normalized seasonal factors of the Winters' multiplicative seasonal model, we provide ten indirect estimation methods in total and suggest the estimated cooling load(1988-1999) based on our various indirect methods.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.163-169
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• 2019

The robust controller synthesis and analysis of the water level process in the U-tube system generator (UTSG) is addressed in this paper. The parameter uncertainties of the steam generator (SG) are modeled as multiplicative perturbations which are normalized by designing suitable weighting functions. The relative errors of the nominal SG model with respect to the other operating power level models are employed to specify the weighting functions for normalizing the plant uncertainties. Then, a robust controller is designed based on ${\mu}$-synthesis and D-K iteration, and its stability robustness is verified over the whole range of power operations. A gain-scheduled controller with $H_{\infty}$-synthesis is also designed to compare its robustness with the proposed controller. The stability analysis is accomplished and compared with the previous QFT design. The ${\mu}$-analysis of the system shows that the proposed controller has a favorable stability robustness for the whole range of operating power conditions. The proposed controller response is simulated against the power level deviation in start-up and shutdown stages and compared with the other concerning controllers.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.1
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• pp.78-86
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• 1995

$H_{\infty}$ Controller of seeker scan-loop is designed using LSDP proposed by McFarlane. The performance and robustness of $H_{\infty}$ controller are analyzed using robustness theorems by Lehtomaki and compared with those of the LQG/LTR controller. Especially, structured singular value .mu. -test of Doyle is used to evaluate robust performance of seeker scan-loop. It is demonstated that seeker scan-loop by $H_{\infty}$ controller is very robust to model uncertainties described by additive and multiplicative perturbations.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.449-458
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• 2007

Bipolar disorder, also known as manic-depressive illness, is a brain disorder that causes unusual shifts in person's mood, energy, and ability to function. Compared with manic episode, the depression episode causes more serious results such as restless, loss of interest or pleasure, or thoughts of death or suicide and the cure rate of depression episode is lower than that of manic episode. Furthermore, a long term use of antidepressants in bipolar patients may result in manic episode. Our interest is to investigate the effect of antidepressant on switch of moods of bipolar patients and to estimate the transition probabilities of switch between moods, depression and (hypo) manic. In this study, three approaches are applied in terms of multi state model. Parametric model is applied using left censoring data and nonparametric model is implemented under illness-death model with counting process. In order to estimate the effect of covariates, a multiplicative model is used. These all methods have similar results.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.1-17
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• 2013

In this article, several types of hybrid forecasting models are suggested. In particular, hybrid models using the generalized additive model (GAM) are newly suggested as an alternative to those using neural networks (NN). The prediction performances of various hybrid and non-hybrid models are evaluated using simulated time series data. Five different types of seasonal time series data related to an additive or multiplicative trend are generated over different levels of noise, and applied to the forecasting evaluation. For the simulated data with only seasonality, the autoregressive (AR) model and the hybrid AR-AR model performed equivalently very well. On the other hand, if the time series data employed a trend, the SARIMA model and some hybrid SARIMA models equivalently outperformed the others. In the comparison of GAMs and NNs, regarding the seasonal additive trend data, the SARIMA-GAM evenly performed well across the full range of noise variation, whereas the SARIMA-NN showed good performance only when the noise level was trivial.