• Journal of Advanced Marine Engineering and Technology
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• v.27 no.3
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• pp.388-394
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• 2003

Hydraulic system is difficult to obtain a suitable performance due to the nonlinearity load pressure change and system parameter variation. The requirement of control a1gorithm has been complex in order to satisfy the performance. The adaptive control is a control method which is suggested to achieve the control object under the plant characteristics change. In spite of the case that plant characteristics and the degree of variation are difficult to grasp. the adaptive control could keep the characteristics of closed-loop system generally. In this study. a method of combined generalized minimum variance adaptive control (GMVAC) and output error feedback is proposed, in order to solve the problem of non-minimum phase of plant and the vibration and overshoot in initial response. The control performance according to the variation of characteristics of plant is evaluated by changing the supply pressure. The experimental results show the effectiveness of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2093-2098
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• 2005

In this paper, $H_{2}$ designs for the one-degree-of-freedom decoupling control systems are treated for the generalized plant. The optimal $H_{2}$ controller is obtained together with the ones that yield finite $H_{2}$ cost functions under compact assumptions. It is shown that the optimal closed transfer matrix is strictly proper under the reasonable order assumptions on the generalized plant.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.370-372
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• 1986

In this paper we propose a Generalized Minimum Variance Self-tuning Control of the system with an autoregressive noise model. To establish a Generalized Minimum Variance Control, the control input is also included in a cost function and a novel identity is introduced. The effectiveness of this algorithm is demonstrated by the computer simulation.

• Nuclear Engineering and Technology
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• v.28 no.3
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• pp.339-348
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• 1996

Plant monitoring algorithm developments seem to be saturated which means that display system to show the results from the algorithm should be the well-defined and interactive tools for operator's diagnosing, controlling, restoring the abnormal plant situations. On the other hand, very little generalized display design concepts and evaluations are available. Events that are unfamiliar to operators and that has not been anticipated by designers may cause great threats to the nuclear power plant system safety operation. The abstraction hierarchy, considered most popular display design methodology but not generalized for nuclear power plant design space, has ken proposed as a representation frame work that can be adopted to design interfaces and supports operators in diagnosing overlooked events that should have been considered to operate plant safely. However most practical plant display systems do not fully stick to this design concept but partially rely on their philosophy from design experiences. Abstraction hierarchy display design concept will be do scribed and the trend of Advanced Control Room(ACR) CRT design will also be presented with the conventional display for the several type of plants. Consequently this complementary material should be of interest to designer and regulators concerned with nuclear power plant.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.1-4
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• 1995

We propose a new design method for a generalized predictive control (GPC) system based on the parametrization of two-degree-of freedom control systems. The objective is to design the GPC system which guarantees the stability of the control system for a perturbed plant. The design procedure of our proposed method consists of three steps. First, we design a basic controller for a nominal plant using the LQG method and parametrize a whole control system. Next, we identify the deviation between the perturbed plant and the nominal one using a closed-loop identification method and design a free parameter of parametrization to stabilize the closed-loop system. Finally, we design a feedforward controller so as to incorporate GPC technique into our controller structure. A numerical example is presented to show the effectiveness of our proposed method.

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.251-258
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• 2016

It is important to verify the identity of plant-based multivitamins prepared with a natural-concept and popular for daily consumption because they are easily purchased in markets with imperfect information. For this study, a generalized partially double-index model (GPDIM) was employed as a main statistical method to identify the contribution of vitamins and phytochemicals to antioxidant potentials using data on antioxidant capacities and chemical fingerprinting. A bootstrapping approach via sufficient dimension reduction is adopted to estimate the two unknown coefficient vectors in the GPDIM. Fifth order polynomial regressions are fitted to measure the contributions of vitamins and phytochemicals after estimating the coefficient vectors with the two double indices.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.1
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• pp.124-132
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• 2004

A hydraulic system is difficult to keep the performance due to non-linearity, load pressure which changes according to working condition and system parameter variation, the requirement of control algorithm has been risen in order to satisfy them. An adaptive control is a control method which is suggested to achieve a control object though plant characteristics change. In spite of the case that plant characteristics and the degree of variation are difficult to grasp, adaptive control can keep the characteristics of closed-loop system regularly. In this study GMVAC(generalized minimum variance adaptive control) combined with output error feedback is proposed in order to solve problems of non-minimum phase, vibration and overshoot in initial response of the plant. The control performance according to the variation of characteristics of the plant is evaluated by changing the supply pressure only.

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.706-712
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• 2011

Necessary and sufficient conditions for the existence of diagonal, block-diagonal, and triangular decoupling controllers in linear multivariable systems for the most general setting are presented. The plant model in this study is sufficiently general to accommodate non-square plant and non-unity feedback cases with one-degree-of-freedom (1DOF) or two-degree-of-freedom (2DOF) controller configuration. The existence condition is described in terms of rank conditions on the coefficient matrices in partial fraction expansions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.967-977
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• 2000

In this paper, we apply a mixed $H_2/H_{\infty}$ control to a generalized plant of inverted pendulum system represented by an LFR(Linear Fractional Representation). First, in order to obtain the generalized plant, the linear model of the inverted pendulum represented by an LFR(Linear fractional Representation) is derived. In LFR, we consider system uncertainties as three nonlinear components and a pendulum mass uncertainty. Augmenting the LFR model by adding weighting functions, we get a generalized plant. And then, we design a mixed $H_2/H_{\infty}$ controller for the generalized plant. In order to design the mixed $H_2/H_{\infty}$ controller, we use the LMI technique. To evaluate control performances and robust stability of the mixed $H_2/H_{\infty}$ controller designed, we compare it with the $H_{\infty}$ controller through the simulation and experiment. In the result, with the fewer feedback information, the mixed $H_2/H_{\infty}$ controller shows the better control performances and robust stability than the $H_{\infty}$ controller in the sense of pendulum angle.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.8
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• pp.557-562
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• 1988

This paper presents a class of discrete adaptive controller that can be applied to a plant without sufficient a priori information. It is well known that the GMV(Generalized Minmum Variance) contrlller performs satisfactorily if the plant time delay is known. By introducing the long-range prediction into the GMV controller, robustness to the time delay can be improved, although optimality is lost. Such an idea motivates a predictive control system to be proposed here, where the system minimizes multi-stage cost via the GMV approach. Moreover, the detuning control weight is determined by an on-line tuning method. It is shown that robustness, computational efficiency, and performance of the resulting control system are improved as compared with those of the GPC(Generalized Predictive Control)system.