• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.414-417
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• 1997

We propose a decentralized $H_{\infty}$ state estimation method in the multisensor state estimation problem. The proposed method bounds the maximum energy gain from unknown external disturbances to the estimation errors in the suboptimal case. And we formulate the decentralized state estimation method in the general case of different global and local models using alternative gain equation of the $H_{\infty}$ state estimator which can calculate global state estimates from the the linear combination of local state estimates. In addition, the proposed update equation between global and local Riccati solutions can reduce unnecessary calculation burden efficiently.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.8
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• pp.682-691
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• 2001

Most of radiant floor heating systems are operated in the intermittent heating mode in Korea. The application possibility of predictive suboptimal control for Koran residential house was investigated by computer simulation and experiment. For this study, TRNSYS program was used and an experimental facility consisting of tow rooms ($3\times4.4\times2.8 m$) identical in construction was built. The facility enabled simultaneous comparison of two different control method. And real multi residential hose was investigated. Results showed that outdoor air temperature prediction control was superior to the conventional control for radiant floor heating system operated in the intermittent heating mode. New control system resulted in good thermal environment and les energy consumption.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.9
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• pp.836-844
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• 2001

For the radiant floor heating system, the possibility of suboptimal prediction control was investigated by computer simulation and experiment. For this study, TRANSYS program was used and an experimental facility consisting of two rooms (3$\times$4.4$\times$2.8m) was built. The facility enabled simultaneous comparison of two different control strategies which implemented in a separate room. Results showed that outdoor air temperature prediction control was superior to the conventional outdoor air temperature compensation control for radiant floor heating system. However, more research for fine prediction of outside air temperature was required in the future.

• Journal of Electrical Engineering and information Science
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• v.3 no.3
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• pp.306-315
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• 1998

In this paper, a unified approach to the H\ulcorner controller design is proposed under the $\delta$-form for both continuous and discrete systems. Most of important basic concepts of H\ulcorner control, such as inner, co-inner, GCARE and GFARE, are reformulated by the unified form. The NLCF(Normalized left Comprime Factor) plant description has been reviewed in the $\delta$-form, and some corresponding results are proposed. And the unified H\ulcorner controller is designed which is based on the McFarlane and Glover{1]. The state-space parameterization for all suboptimal controllers is given under the NLCF model which may not be strictly proper, and the central controller is derived by using the solution to Hankel norm approximation problem[2]. The unified controller is applied to the industrial boiler control problem to exemplify the performance of the controller.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.17-23
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• 2013

It has been studied that retailer's using a suboptimal (R, T) policy is often more desirable to make the best use of information flows than the locally optimal (s, S) policy in a two-stage serial supply chain. In this paper, by performing an extensive computational study, we tabulate the benefit of the retailer's using (R, T) policy instead of (s, S) policy in a supply chain with information sharing, and compare it to a maximum possible benefit that could be achieved in a centralized supply chain. We can understand the mechanisms of how the cost parameters and demand variance affect the benefit of the retailer's using (R, T) policy instead of (s, S) policy, by comparing decentralized and centralized systems.

• ETRI Journal
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• v.39 no.6
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• pp.782-793
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• 2017

This paper considers the use of the Partial Transmit Sequence (PTS) technique to reduce the Peak-to-Average Power Ratio (PAPR) of an Orthogonal Frequency Division Multiplexing signal in wireless communication systems. Search complexity is very high in the traditional PTS scheme because it involves an extensive random search over all combinations of allowed phase vectors, and it increases exponentially with the number of phase vectors. In this paper, a suboptimal metaheuristic algorithm for phase optimization based on an improved harmony search (IHS) is applied to explore the optimal combination of phase vectors that provides improved performance compared with existing evolutionary algorithms such as the harmony search algorithm and firefly algorithm. IHS enhances the accuracy and convergence rate of the conventional algorithms with very few parameters to adjust. Simulation results show that an improved harmony search-based PTS algorithm can achieve a significant reduction in PAPR using a simple network structure compared with conventional algorithms.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.171-179
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• 2008

This paper addresses the synthesis of an iterative learning controller for a class of linear systems with norm-bounded parameter uncertainties. We take into account an iterative learning algorithm with current cycle feedback in order to achieve both robust convergence and robust stability. The synthesis problem of the developed iterative learning control (ILC) system is reformulated as the ${\gamma}$-suboptimal $H_{\infty}$ control problem via the linear fractional transformation (LFT). A sufficient convergence condition of the ILC system is presented in terms of linear matrix inequalities (LMIs). Furthermore, the ILC system with fast convergence rate is constructed using a convex optimization technique with LMI constraints. The simulation results demonstrate the effectiveness of the proposed method.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.233-234
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• 2006

In this paper, we propose a novel PAPR reduction scheme, which requires no change of a receiver structure or no additional information transmission. The approach we employed is clipping in the time and frequency domains within EVM, which is a suboptimal method with lower computational complexity compared to the optimal method. The simulation results demonstrated that the proposed method is more effective at lower modulation levels with larger constellation errors.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.103-109
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• 2015

In this paper, a novel method for the classification of term and preterm birth is proposed based on time-frequency analysis of electrohysterogram (EHG) using multivariate empirical mode decomposition (MEMD). EHG is a promising study for preterm birth prediction, because it is low-cost and accurate compared to other preterm birth prediction methods, such as tocodynamometry (TOCO). Previous studies on preterm birth prediction applied prefilterings based on Fourier analysis of an EHG, followed by feature extraction and classification, even though Fourier analysis is suboptimal to biomedical signals, such as EHG, because of its nonlinearity and nonstationarity. Therefore, the proposed method applies prefiltering based on MEMD instead of Fourier-based prefilters before extracting the sample entropy feature and classifying the term and preterm birth groups. For the evaluation, the Physionet term-preterm EHG database was used where the proposed method and Fourier prefiltering-based method were adopted for comparative study. The result showed that the area under curve (AUC) of the receiver operating characteristic (ROC) was increased by 0.0351 when MEMD was used instead of the Fourier-based prefilter.

• The Korean Journal of Financial Management
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• v.25 no.4
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• pp.145-182
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• 2008

As the life expectancy increases resulting in the aged society, the post-retirement life became one of the most important concerns of people. The long-term investment vehicles such as retirement savings and pension plans have been introduced to meet such demand of society. This paper examines the impact of asset allocation strategies on the long-term investment performance. Because of the unusually long investment horizon and the compounding effect, a suboptimal asset mix in a retirement plan can be a very costly and irreversible mistake. Instead of relying on anecdotal evidence to evaluate the merits of different allocation strategies, this paper performs various tests including stochastic dominance tests using both actual data and Monte Carlo simulated data that best fit the historical experience. The results indicate 1) the long-term investments perform better than the short-term investments, 2) the optimal asset allocation strategy for the long-term investments should be highly equity dominated.