• 대한전기학회논문지
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• 제38권7호
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• pp.557-568
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• 1989

Using Power Spectrum Analysis, conditions of parameter convergence for a Model Reference Adaptive Control (MRAC) system are described. The general Persistent Excitation (PE) condition given in time domain can be transformed to the positiveness of auto-correlation matrix which is represented in frequency domain by the spectra of reference input signal. For an MRAC system designed with relative degree one, the existence and the uniqueness of parameter nominal values due to the variation of input spectra can be analyzed by the PE condition in frequency domain. If the input signal has 2n spectra or more, it can be shown that the nominal values exist independent of adaptive gain, input amplitudes, and magnitudes or numbers of their spectra.

• 한국태양에너지학회 논문집
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• 제25권1호
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• pp.1-10
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• 2005

In this paper, 150W photovoltaic system using neural network tracker is proposed, the system designed as the normal line of the solar cell always runs parallel the ray of the sun. This design can minimize the cosine loss of the system output results of solar cell are sensitive to the change of weather and insolation condition don't react rapidly to parameter condition change such as system circumstance and deterioration. To achieve precise operation of photovoltaic tracker system using method of intelligent control, Neural Network is used in the design of the photovoltaic tracker system drive. The control performance of this system drive influenced by the environment parameter such as weather condition and motor parameter variations. we used synchronous motor in this tracker and the experimental results show that the fixing system shows 10,159[Wh] and tracking system shows 12,360[Wh] electricity.

• 한국안전학회지
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• 제30권5호
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• pp.131-137
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• 2015

For the evaluation of safety margin of a nuclear power plant using a conservative methodology, the influence of applied assumptions such as initial conditions and boundary conditions needs to be assessed deliberately. Usually, a combination of the most conservative initial conditions is determined, and the safety margin for the transient is evaluated through the analysis for this conservative conditions. In existing conservative methodologies, a most-conservative condition is searched through the analyses for the maximum, minimum, and nominal values of the major parameters. In the present study, we investigates a new approach which can be applied to choose a most-conservative initial condition effectively when a best-estimate computer code and a conservative evaluation methodology are utilized for the evaluation of safety margin of transients. By constituting the band of various initial conditions using the random sampling of input parameters, the sensitivity study for various parameters are performed systematically. A method of sampling the value of control or operation parameters for a certain range is adopted by use of MOSAIQUE program, which enables to minimize the efforts for achieving the steady-state for various different conditions. A representative control parameter is identified, which governs the reactor coolant flow rate, pressurizer pressure, pressurizer level, and steam generator level, respectively. It is shown that an appropriate distribution of input parameter is obtained by adjusting the range and distribution of the control parameter.

• Nuclear Engineering and Technology
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• 제50권4호
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• pp.599-605
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• 2018

Fault diagnosis depends critically on the selection of sensors monitoring crucial process variables. Boolean network (BN) is composed of nodes and directed edges, where the node state is quantized to the Boolean values of True or False and is determined by the logical functions of the network parameters and the states of other nodes with edges directed to this node. Since BN can describe the fault propagation in a sensor network, it can be applied to propose sensor selection strategy for fault diagnosis. In this article, a sufficient condition for parameter identifiability of BN is first proposed, based on which the sufficient condition for fault identifiability of a sensor network is given. Then, the fault identifiability condition induces a sensor selection strategy for sensor selection. Finally, the theoretical result is applied to the fault diagnosis-oriented sensor selection for a nuclear heating reactor plant, and both the numerical computation and simulation results verify the feasibility of the newly built BN-based sensor selection strategy.

• 제어로봇시스템학회논문지
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• 제12권5호
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• pp.411-418
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• 2006

There are mainly two types of bang-bang controllers for nominal linear time-invariant (LTI) system. Optimal bang-bang controller is designed based on optimal control theory and suboptimal bang-bang controller is obtained by using Lyapunov stability condition. In this paper, the suboptimal bang-bang control method is extended to LTI system involving both control input saturation and structured real parameter uncertainties by using Lyapunov robust stability condition. Two robust optimal bang-bang controllers are derived by minimizing the time derivative of Lyapunov function subjected to the limit of control input. The one is developed based on the classical quadratic stability(QS), and the other is developed based on the affine quadratic stability(AQS). And characteristics of the two controllers are compared. Especially, bounds of parameter uncertainties which theoretically guarantee robust stability of the two controllers are compared quantitatively for 1DOF vibrating system. Moreover, the validity of robust optimal bang-bang controller based on the AQS is shown through numerical simulations for this system.

• 대한수학회보
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• 제49권5호
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• pp.1041-1055
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• 2012

The parameter lower (upper) distribution set corresponds to the cylindrical lower or upper local dimension set for a self-similarmeasure on a self-similar set satisfying the open set condition.

• Industrial Engineering and Management Systems
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• 제6권2호
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• pp.119-124
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• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2000년도 추계학술대회 논문집(Proceeding of the KOSME 2000 Autumn Annual Meeting)
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• pp.135-142
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• 2000

The adjusting parameter set which enable control systems to locate on stability limit can be derived from theoretical or trial methods for an existing real system. The data from the results are much available to keep a system in the Proper stability condition even to site engineers who are inexperienced in the control system. In this paper, a general one loop control system was adopted for a model system the process of which was assumed to consist of a time-delay element and a first order-lag element in series. After obtaining the corresponding parameter set for the model system by mathematical procedures, their loci on the parameter space was taken according to frequency change. The parameter set loci of stability limit showed unique pattern, and particularity , the curves on the Kg-Ti parameter space were able to be generalized in the form of, an unique exponential formula. These properties were also compared with the results taken from experimental procedures by Nyquist response method and Ziegler & Nichols method on the time domain, and both results were confirmed to be nearly same.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 A
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• pp.388-390
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• 1995

A new control scheme based on dead beat control with adaptive parameter estimation for PWM Inverter is proposed. The proposed scheme updates dead beat control parameters continouously, and make PWM inverter excellent performance at any load or parameter condition. Simulation results show very attractive features in this proposed scheme.

• 대한산업공학회지
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• 제25권3호
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• pp.330-335
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• 1999

The goal of the study is to determine the most sensitive parameter to represent the degree of muscle force and fatigue. Various numerical parameters such as the first coefficient of Autoregressive (AR) Model, Root Mean Square (RMS), Zero Crossing Rate (ZCR), Mean Power Frequency (MPF), Median Frequency (MF) were tested in this study. Ten healthy male subjects participated in the experiment. They were asked to extend their trunk by using the right and left erector spinae muscles during a sustained isometric contraction for twenty seconds. The force levels were 15%, 30%, 45%, 60%, and 75% of Maximal Voluntary Contraction (MVC), and the order of trials was randomized. The results showed that RMS was the best parameter to measure the force level of the muscle, and that the first coefficient of AR model was relatively sensitive parameter for the fatigue measurement at less than 60% MVC condition. At the 75% MVC, however, both MPF and the first coefficient of AR Model showed the best performance in quantification of muscle fatigue. Therefore, the sensitivity of measurement can be improved by properly selecting the parameter based upon the level of force during a sustained isometric condition.