• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.315-322
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• 2004

A direct adaptive state-feedback controller for highly nonlinear systems is proposed. This paper considers uncertain or ill-defined nonaffine nonlinear systems and employs a static fuzzy logic system (FLS). The employed FLS estimates. and adaptively cancels an unknown plant nonlinearity using its proved universal approximation property. A control law and adaptive laws for unknown fuzzy parameters and bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov. The tracking error is guaranteed to be uniformly asymptotically stable rather than uniformly ultimately bounded with the aid of an additional robustifying control term. No a priori knowledge of an upper bound on an lumped uncertainty is required.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.273-282
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• 1996

This work is conceded with the estimation of output derivatives and their use for the design of robust controller for linear systems with system uncertainties due to modeling errors and disturbances. It is assumed that a nominal transfer function model and quantitative bounds for system uncertainties and known. The developed control schemes are shown to achieve regulation of the system output and ensures boundedness of the system states without imposing any structural conditions on system uncertainties and disturbances. Output derivative estimation is first conducted through restructuring of the plant in a specific parameterization. They are utilized for constructing robust nonlinear high-gain feedback controller of a SMC(Sliding Mode Control)type. The performances of the developed controller are evaluated and shown to be effective and useful through simulation study.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.972-979
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• 1999

QFT(Quantitative Feedback Theory) is a very practical design technique that emphasizes the use of feedback for achieving the desired system performance tolerances in despite of plant uncertainty and disturbance. The fundamental concept of QFT is a loop shaping procedure that a suitable controller can be found by shaping a nominal loop transfer function. The loop shaping synthesis involves the identification of a structure and the specialization of parameter optimization of a desired system. This paper presents an improved loop shaping approach of QFT with model validation using GA(Genetic Algorithm). The method presented in this paper removes the problems of iterative operation, transformation error, and model validation in the conventional methods without consideration of frequency domain.

• Nuclear Engineering and Technology
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• v.29 no.1
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• pp.1-6
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• 1997

This paper presents a new dynamic approach for assessing feasibility associated with the implementation of accident management strategies by the operators. This approach includes the combined use of both the concept of reliability physics and a dynamic event tree generation scheme. The reliability physics is based on the concept of a comparison between two competing variables, i.e., the requirement and the achievement parameter, while the dynamic event tree generation scheme on the continuous generation of the possible event sequences at every branch point up to the desired solution. This approach is applied to a cavity flooding strategy in a reference plant, which is to supply water into the reactor cavity using emergency fire systems in the station blackout sequence. The MAAP code and Latin Hypercube sampling technique are used to determine the uncertainty of the requirement parameter. It has been demonstrated that this combined methodology may contribute to assessing the success likelihood of the operator actions required during accidents and therefore to developing the accident management procedures.

• Nuclear Engineering and Technology
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• v.29 no.1
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• pp.25-34
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• 1997

This study presents a new approach for expert opinion elicitation process to assess an uncertainty inherent in accident management. The need to work with rare event and limited data in accident management leads analysis to use expert opinions extensively. Unlike the conventional approach using point-valued probabilities, the study proposes the concept of fuzzy probability to represent expert opinion. The use of fuzzy probability has an advantage over the conventional approach when an expert's judgment is used under limited dat3 and imprecise knowledge. The study demonstrates a method of combining and propagating fuzzy probabilities. finally, the proposed methodology is applied to the evaluation of the probability of a bottom head failure for the flooded case in the Peach Bottom BWR nuclear power plant.

• 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.

• 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 Intelligence and Information Systems
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• v.7 no.1
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• pp.81-95
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• 2001

Plant construction projects usually take much higher uncertainty and risks than the projects from other domains. This implies the importance of plant construction project management should be more emphasized than the other domain. Especially, the overall successes of the projects often depend on the performance of process planning and scheduling performed at the initial stage of the project. However, most plant construction projects suffer great difficulties in establishing proper process planning and scheduling timely because of unstructureness and dynamicity of environment of the project itself In this paper, we propose a knowledge-based process planning and scheduling approach in a plant construction domain to cope this problem. First, we modulize process planning knowledge and present the knowledge representation scheme. Second, we propose an inferencing mechanism to build a process planning for plant construction based on the represented process planning knowledge. Since our approach automate the initial process planning, which was usually done by manual way, it can improve the correctness and also completeness of the process plan and schedule by reducing the time to plan and allowing simulations on the various situation. We also design and implement this our approach as a real working system, and it is successfully applied to real plant construction cases from a leading construction company in Korea. Based on this success, we expect our approach can be easily applied to the projects of other areas, while contributing to enhancement in productivity and quality of project management.

• Journal of Radiation Protection and Research
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• v.28 no.3
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• pp.189-197
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• 2003

The Level 3 PSA being termed accident consequence analysis is defined to assess effects on health and environment caused by radioisotopes released from severe accidents of nuclear power plants. In this study consequence analysis on health effects depending on release characteristics of radioisotopes has been peformed using the 3 MACCS code in severe accidents. The results of this study may contribute to identifying the relative importance of various parameters occurred in consequence analysis as well as to assessing risk reduction accident management strategies. Especially three parameters for the purpose of consequence analysis, such as the release height, the heat content, and the duration time, are used to analyze the variation of early fatalities and latent cancer fatalities. Also, in this study risk assessment using the concept, 'products of uncertainty and consequences', has been performed using consequence of MACCS and frequency on source term category 19 scenarios from IPE (Individual Plant Examination) analysis.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.3
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• pp.88-97
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• 2013

This paper presents a robust air-to-fuel ratio (AFR) control algorithm for managing exhaust gas recirculation (EGR) systems. In order to handle production tolerance, deterioration and parameter-varying characteristics of the EGR system, quantitative feedback theory (QFT) is applied for designing the robust AFR control algorithm. A plant model of EGR system is approximated by the first order transfer function plus time-delay (FOPTD) model. EGR valve position and AFR of exhaust gas are used as input/output variables of the plant model. Through engine experiments, parameter uncertainty of the plant model is identified in a fixed engine operating point. Requirement specifications of robust stability and reference tracking performance are defined and these are fulfilled by the following steps: during loop shaping process, a PID controller is designed by using a nominal loop transmission function represented on Nichols chart. Then, the frequency response of closed-loop transfer function is used for designing a prefilter. It is validated that the proposed QFT-based AFR control algorithm successfully satisfy the requirements through experiments of various engine operating points.