• 대한전자공학회논문지
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• 제25권9호
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• pp.1039-1045
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• 1988

In the original incremental generalized predictive control, the receding horizon predictive control is introduced as a control law. But in this paper, we propose a generalized predictive self-tuning control using full-valued incremental controls. The control law is a mean horizon predictive control. The effectiveness of this algorithm in a variable time delay or load disturbances environment is demonstrated by computer simulation. The controlled plant is a nonminimum phase system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.663-668
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• 1990

This paper deals with the application of a Generalized Predictive Control (CPC) to a Pressurized Water Reactor (P.W.R) Nuclear Power Plant. Generalized Predictive Control is a sort of Explicit Self-Tuning Control. Current self-tuning algorithms lack robustness to prior choices of either dead-time (input time delay of a plant) or model order. GPC is shown by simulation studies to be superior to accepted self-tuning techniques such as minimum variance and pole-placement from the viewpoint that it is robust to prior choices of dead-time or model order. In this paper a GPC controller is designed to control the P.W.R. nuclear power rlant with varying dead-time and through the designing procedure the designer is free from the constraint of knowing the exact dead-time. The controller is constructed based on the 2nd order linear model approximated in the vicinity of operating point. To ensure that this low-order model describes the complex real dynamics well enough for control purposes, model parameters are updated on-line with a Recursive Least Squares algorithm. Simulation results are successful and show the possibilities of the GPC control application to actual plants with varying or unknown dead-time.

• 제어로봇시스템학회논문지
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• 제3권3호
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• pp.272-279
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• 1997

In this paper, a fuzzy generalized predictive control (FGPC) for non-linear plants is proposed. In the proposed method, the receding horizon control is applied to the control part, while fuzzy systems are used for the predictor part. It is suggested that the fuzzy predictor is time-varying affine with respect to input variables for easy computation of control inputs. Since the receding horizon control can be obtained only with a predictor instead of a plant model, the fuzzy predictor is obtained directly from input-output data without identifying a plant model. A parameter estimation algorithm is used for identifying the fuzzy predictor. The control inputs of the FGPC are computed by minimizing a receding horizon cost function with predicted plant outputs. The proposed controller has a similar architecture to the generalized predictive control (GPC) except for the predictor synthesis method, and thus may possess inherent good properties of the GPC. Computer simulations show that the performance of the FGPC is satisfactory.

• 시스템엔지니어링학술지
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• 제16권1호
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• pp.84-97
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• 2020

This paper aims to develop an optimized inventory management method for safety critical Instrument and Control (I&C) components. In this regard, the paper focuses on estimating the consumption rate of I&C components using demand forecasting methods. The target component for this paper is the Foxboro SPEC-200 controller. This component was chosen because it has highest consumption rate among the safety critical I&C components in Korean OPR-1000 NPPs. Three analytical methods were chosen in order to develop the demand forecasting methods; Poisson, Generalized Linear Model (GLM) and Bootstrapping. The results show that the GLM gives better accuracy than the other analytical methods. This is because the GLM considers the maintenance level of the component by discriminating between corrective and preventive.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2521-2525
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• 2005

In this paper, we presented a predictive control technique, which is based on wavelet neural network (WNN), for the control of chaotic systems whose precise mathematical models are not available. The WNN is motivated by both the multilayer feedforward neural network definition and wavelet decomposition. The wavelet theory improves the convergence of neural network. In order to design predictive controller effectively, the WNN is used as the predictor whose parameters are tuned by error between the output of actual plant and the output of WNN. Also the training method for the finding a good WNN model is the Extended Kalman algorithm which updates network parameters to converge to the reference signal during a few iterations. The benefit of EKF training method is that the WNN model can have better accuracy for the unknown plant. Finally, through computer simulations, we confirmed the performance of the proposed control method.

• 식물조직배양학회지
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• 제24권4호
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• pp.225-231
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• 1997

For genetic engineering to be commercially viable, an efficient transformation system is needed to produce transgenic plane from diverse genotypes ("generalized protocol"). Development of such a system requires optimization of a number of components such as gene transfer agent, plant tissues competent for both regeneration and transformation, and control of transgene expression. Although several novel gene transfer methods have been developed for plane, a majority of stably transformed plane express the introduced genes at low levels. Moreover, silencing of selectable marker genes shortly after their incorporation into plant chromosomes may result in low recovery of transgenic tissues from selection. Matrix attachment regions (MARs) are DNA sequences that bind to the cell's proteinaceous nuclear matrix to form DNA loop domains. MARs have been shown to increase transgene expression in tobacco cells, and reduce position in mature transgenic plants. Flanking an antibiotic resistance transgene with MARs should therefore lead to improved rates of transformation in a diversity of species, and may permit recalcitrant species and genotypes to be successfully transformed. Literature review and recent data from my laboratory suggest that MARs can serve as a transformation booster in recalcitrant plant species.

• 한국지진공학회논문집
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• 제24권1호
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• pp.1-8
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• 2020

In 2016, an earthquake occurred at Gyeongju, Korea. At the Wolsong site, the observed peak ground acceleration was lower than the operating basis earthquake (OBE) level of Wolsong nuclear power plant. However, the measured spectral acceleration value exceeded the spectral acceleration of the operating-basis earthquake (OBE) level in some sections of the response spectrum, resulting in a manual shutdown of the nuclear power plant. Analysis of the response spectra shape of the Gyeongju earthquake motion showed that the high-frequency components are stronger than the response spectra shape used in nuclear power plant design. Therefore, the seismic performance evaluation of structures and equipment of nuclear power plants should be made to reflect the characteristics of site-specific earthquakes. In general, the floor response spectrum shape at the installation site or the generalized response spectrum shape is used for the seismic performance evaluation of structures and equipment. In this study, a generalized response spectrum shape is proposed for seismic performance evaluation of structures and equipment for nuclear power plants. The proposed response spectrum shape reflects the characteristics of earthquake motion in Korea through earthquake hazard analysis, and it can be applied to structures and equipment at various locations.

• 전기전자학회논문지
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• 제26권3호
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• pp.349-354
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• 2022

화력발전소의 보일러 모델은 로직도 작성, 플랜트 튜닝, 제어이론 적용 등 다양한 분야에 사용된다. 특히 정확한 제어를 위해서는 정확한 모델이 필요하다. 수학적 모델은 화력발전소 시스템의 비선형성, 복잡성, 시변특성 등으로 인하여 시스템을 정확하게 표현하는데 한계가 있다. 이런 시스템에 대하여 신경망을 이용한 모델링 방법은 좋은 대안이 될 수 있다. 본 논문에서는 화력발전소 보일러의 증기계통을 신경망 알고리즘의 한 종류인 GRNN을 이용하여 모델링하였다. 보일러의 과열기와 재열기, 과열저감기, 드럼을 모델링하여 540[MW]급 화력발전소에서 취득한 데이터를 이용하여 학습하고 검증하였다. 검증결과 제안한 모델의 출력이 보일러의 실제 출력과 잘 일치함을 알 수 있었다.

• Management Science and Financial Engineering
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• 제5권2호
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• pp.25-41
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• 1999

This paper generalizes the classic two-stage multicommodity distribution system design problem to the one that includes plant locations as well as distribution center locations. Accommodating plant location leads to subproblems which are mixed are mixed integer. Hence. no LP-type subproblems are avail-able, and therefore standard Benders decomposition no longer applies. We develop new solution method which combines an integer L-shaped method with Benders decomposition to suit the purpose, and pre-sent the test results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.457-460
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• 1989

This note considers the problems of finding a pole assignment controller for a plant with parameter perturbations. Based on Kharitonov's theorem and its generalized results, we propose a design method of controller using linear transformations such that it guarantees the desired damping ratio.