• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.40.5-40
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• 2001

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-S) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.4
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• pp.38-49
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• 1998

A fossil power plant can be modeled by a lot of algebraic equations and differential equations. When we simulate a large, complicated fossil power plant by a computer such as workstation or PC, it takes much time until overall equations are completely calculated. Therefore, new processing systems which have high computing speed is ultimately needed for real-time or high-speed(faster than real-time) simulators. This paper presents an enhanced strategy in which high computing power can be provided by parallel processing of DSP processors with communication links. DSP system is designed for general purpose. Parallel DSP system can be easily expanded by just connecting new DSP modules to the system. General urpose DSP modules and a VME interface module was developed. New model and techniques for the task allocation are also presented which take into account the special characteristics of parallel I/O and computation. As a realistic cost function of task allocation, we suggested 'simulation period' which represents the period of simulation output intervals. Based on the development of parallel DSP system and realistic task allocation techniques, we cound achieve good efficiency of parallel processing and faster simulation speed than real-time.

• Journal of Radiation Protection and Research
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• v.41 no.2
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• pp.117-121
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• 2016

Background: Definition and grouping of initiating events (IEs) are important basics for probabilistic safety assessment (PSA). An IE in a spent fuel reprocessing plant (SFRP) is an event that probably leads to the release of dangerous material to jeopardize workers, public and environment. The main difference between SFRPs and nuclear power plants (NPPs) is that hazard materials spread diffusely in a SFRP and radioactive material is just one kind of hazard material. Materials and Methods: Since the research on IEs for NPPs is in-depth around the world, there are several general methods to identify IEs: reference of lists in existence, review of experience feedback, qualitative analysis method, and deductive analysis method. While failure mode and effect analysis (FMEA) is an important qualitative analysis method, master logic diagram (MLD) method is the deductive analysis method. IE identification in SFRPs should be consulted with the experience of NPPs, however the differences between SFRPs and NPPs should be considered seriously. Results and Discussion: The plutonium uranium reduction extraction (Purex) process is adopted by the technics in a model reprocessing plant. The first extraction cycle (FEC) is the pivotal process in the Purex process. Whether the FEC can function safely and steadily would directly influence the production process of the whole plant-production quality. Important facilities of the FEC are installed in the equipment cells (ECs). In this work, IEs in the FEC process were identified and categorized by FMEA and MLD two methods, based on the fact that ECs are containments in the plant. Conclusion: The results show that only two ECs in the FEC do not need to be concerned particularly with safety problems, and criticality, fire and red oil explosion are IEs which should be emphatically analyzed. The results are accordant with the references.

• Journal of Veterinary Science
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• v.21 no.5
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• pp.74.1-74.13
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• 2020

Background: The quality of a vaccine depends strongly on the effects of the adjuvants applied simultaneously with the antigen in the vaccine. The adjuvants enhance the protective effect of the vaccine against a viral challenge. Conversely, oil-type adjuvants leave oil residue inside the bodies of the injected animals that can produce a local reaction in the muscle. The long-term immunogenicity of mice after vaccination was examined. ISA206 or ISA15 oil adjuvants maintained the best immunity, protective capability, and safety among the oil adjuvants in the experimental group. Objectives: This study screened the adjuvant composites aimed at enhancing foot-and-mouth disease (FMD) immunity. The C-type lectin or toll-like receptor (TLR) agonist showed the most improved protection rate. Methods: Experimental vaccines were fabricated by mixing various known oil adjuvants and composites that can act as immunogenic adjuvants (gel, saponin, and other components) and examined the enhancement effect on the vaccine. Results: The water in oil (W/O) and water in oil in water (W/O/W) adjuvants showed better immune effects than the oil in water (O/W) adjuvants, which have a small volume of oil component. The W/O type left the largest amount of oil residue, followed by W/O/W and O/W types. In the mouse model, intramuscular inoculation showed a better protection rate than subcutaneous inoculation. Moreover, the protective effect was particularly weak in the case of inoculation in fatty tissue. The initial immune reaction and persistence of long-term immunity were also confirmed in an immune reaction on pigs. Conclusions: The new experimental vaccine with immunostimulants produces improved immune responses and safety in pigs than general oil-adjuvanted vaccines.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.38-49
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• 2012

In this study, we analyze statistical characteristics of influent water quality in Daejeon waste water treatment plant and apply a stochastic model for data generation. In the analysis, the influent water quality data from year 2003 to 2008, except for year 2006, are used. Among water quality variables, we find strong correlations between BOD and T-N; T-N and T-P; BOD and T-P; $COD_{Mn}$ and T-P; and BOD and $COD_{Mn}$. We also find that different water quality variables follow different theoretical probability distribution functions, which also depends on whether the seasonal cycle is removed. Finally, we generate the influent water quality data using the multi-season 1st Markov model (Thomas-Fiering model). With model parameters calibrated for the period 2003~2005, the generated data for 2007~2008 are well compared with observed data showing good agreement in general. BOD and T-N are underestimated by the stochastic model. This is mainly due to the statistical difference in observed data itself between two periods of 2003~2005 and 2007~2008. Therefore, we expect the stochastic model can be applied with more confidence in the case that the data follows stationary pattern.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• IE interfaces
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• v.13 no.3
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• pp.320-327
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• 2000

In this research report, we consider multi stage supply chain optimization modeling techniques, and propose a new integrated model. The stages that are normally associated with a supply chain include procurement, production and distribution. In general, there are two distinct set of approaches which manage whole supply chain. One approach is the plant decision and subsequently distribution and inventory decision while the second approach is to address all decisions simultaneously through the integrated model. First, we present a survey of existing models that are treated by independently. And then, we propose an integrated model that is in a moderate size and easy to implement in practice. Finally, we address possible solution methodologies and present some computational test results using CPLEX to see the computational burden from which new algorithmic insight might be come up.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.133-136
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• 2000

The objective of this paper is to present a method for designing robust positioning control systems of a flexible arm using $H_2/H_{\infty}$ and $\mu$ theory. We begin with a description of the flexible arm based on the model identification method and discuss the derivation of the model uncertainty. The validity of the obtained model is confirmed experimentally Next, a robust controller is designed based on the $H_2/H_{\infty}$ and $\mu$ theory by which we can improve robustness of the entire system. On this occasion, we also propose a general plant formation suitable to $H_2/H_{\infty}$ control. Finally, the effectiveness of the proposed design method is verified through experimentation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.10
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• pp.740-747
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• 1988

This paper describes the parameter convergence property for an adaptive identifier and deals with the stability of the adaptive system in terms of the general error model. The Persistent Excitation (PE) condition to guarantee parameter convergence is derived using the Power Spectrum Analysis. In the adaptive identifier designed under the assumptions that the plant has not unmodelled dynamics, it can be shown that the equilibrium points of adjustable parameters are independent on the position or the number of input spectrums, if the adaptive signal is PE. When the plant contains unmodelled dynamics and the same controller is used, the PE condition can still hold but the parameter tuned values are changed with the spectrum.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.3
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• pp.598-625
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• 2014

To support the procedure for determining an optimal liquefaction cycle for FLNG FEED, an ontological modeling method which can automatically generate various alternative liquefaction cycles were carried out in this paper. General rules in combining equipment are extracted from existing onshore liquefaction cycles like C3MR and DMR cycle. A generic relational model which represents whole relations of the plant elements has all these rules, and it is expressed by using the system entity structure (SES), an ontological framework that hierarchically represents the elements of a system and their relationships. By using a process called pruning which reduces the SES to a candidate, various alternative relational models of the liquefaction cycles can be automatically generated. These alternatives were provided by XML-based formats, and they can be used for choosing an optimal liquefaction cycle on the basis of the assessments such as process simulation and reliability analysis.