• Proceedings of the KIEE Conference
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• summer
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• pp.342-344
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• 2004

In conventional small signal stability analysis, system is assumed to be invariant and the state space equations are used to calculate the eigenvalues of state matrix. However, when a system contains switching elements such as FACTS devices, it becomes non-continuous system. In this case, a mathematically rigorous approach to system small signal stability analysis is by means of eigenvalue analysis of the system periodic transition matrix based on discrete system analysis method. In this research, RCF(Resistive Companion Form) method is used to analyse small signal stability of a non-continuous system including switching elements'. Applying the RCF method to the differential and integral equations of power system, generator, controllers and FACTS devices including switching elements should be modeled in the form of state transition matrix. From this state transition matrix eigenvalues which are mapped to unit circle can be calculated.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1648-1649
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• 2007

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM(Support Vector Machines) makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller be with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.32.2-32.2
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• 2011

State dependent Riccati equation (SDRE) control technique has been widely used in the control society. Although it solves nonlinear optimal control problems, which minimizes state error and control efforts simultaneously, it has drawbacks when it is to be applied to the real time systems in that it requires much computational efforts. So the real time system whose computational ability is limited (for example, satellites) cannot afford to use SDRE controller. To solve this problem, a hybrid controller which is based on MSDRE (Modified SDRE) and ANFIS (Adaptive Neuro-Fuzzy Inference System) has been proposed by Abdelrahman et al. (2010). We propose a hybrid controller based on SDRE and ANFIS, and apply the hybrid controller to the hardware attitude simulator to perform a HIL (Hardware-In-the-Loop) simulation. Through HIL simulation, it is demonstrated that the hybrid controller satisfies the control requirement and the computation load is reduced significantly. In addition, the effects of statistical properties of the ANFIS training data to the performance of the ANFIS controller have been analyzed.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2288-2296
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• 2015

This paper proposes a novel systematic modeling approach for an integrated single-stage power converter in order to predict its dynamic characteristics. The basic strategy of the proposed modeling is substituting the internal converters with an equivalent current source, and then deriving the dynamic equations under a standalone operation using the state-space averaging technique. The proposed approach provides an intuitive modeling solution and simplified mathematical process with accurate dynamic prediction. The simulation and experimental results by using an integrated boost-flyback converter prototype provide verification consistent with theoretical expectations.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.5 no.1
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• pp.55-78
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• 2001

Given the anisotropic Poisson equation $-{\nabla}{\cdot}{\mathcal{K}}{\nabla}p=f$, one can convert it into a system of two first order PDEs: the Darcy law for the flux $u=-{\mathcal{K}{\nabla}p$ and conservation of mass ${\nabla}{\cdot}u=f$. A very natural mixed finite volume method for this system is to seek the pressure in the nonconforming P1 space and the Darcy velocity in the lowest order Raviart-Thomas space. The equations for these variables are obtained by integrating the two first order systems over the triangular volumes. In this paper we show that such a method is really a standard finite element method with local recovery of the flux in disguise. As a consequence, we compare two approaches in analyzing finite volume methods (FVM) and shed light on the proper way of analyzing non co-volume type of FVM. Numerical results for Dirichlet and Neumann problems are included.

• Journal of the Korean Mathematical Society
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• v.51 no.4
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• pp.665-678
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• 2014

We present a new space-time discontinuous Galerkin (DG) method for solving the time dependent, positive symmetric hyperbolic systems. The main feature of this DG method is that the discrete equations can be solved semi-explicitly, layer by layer, in time direction. For the partition made of triangle or rectangular meshes, we give the stability analysis of this DG method and derive the optimal error estimates in the DG-norm which is stronger than the $L_2$-norm. As application, the wave equation is considered and some numerical experiments are provided to illustrate the validity of this DG method.

• Nuclear Engineering and Technology
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• v.43 no.3
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• pp.243-256
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• 2011

This paper considers the concept of analog computing based on a cellular neural network (CNN) paradigm to simulate nuclear reactor dynamics using a time-dependent second order form of the neutron transport equation. Instead of solving nuclear reactor dynamic equations numerically, which is time-consuming and suffers from such weaknesses as vulnerability to transient phenomena, accumulation of round-off errors and floating-point overflows, use is made of a new method based on a cellular neural network. The state-of-the-art shows the CNN as being an alternative solution to the conventional numerical computation method. Indeed CNN is an analog computing paradigm that performs ultra-fast calculations and provides accurate results. In this study use is made of the CNN model to simulate the space-time response of scalar flux distribution in steady state and transient conditions. The CNN model also is used to simulate step perturbation in the core. The accuracy and capability of the CNN model are examined in 2D Cartesian geometry for two fixed source problems, a mini-BWR assembly, and a TWIGL Seed/Blanket problem. We also use the CNN model concurrently for a typical small PWR assembly to simulate the effect of temperature feedback, poisons, and control rods on the scalar flux distribution.

• Journal of Korea Technology Innovation Society
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• v.11 no.1
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• pp.72-90
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• 2008

What has been the contribution of industrial innovation to economic growth? Typically, the issue has been approached with growth-accounting methods augmented to include a "stock of knowledge". An independent estimate of the rate of return to R&D is found in order to impute patents granted to the accumulation of knowledge. Griliches(1973) then uses a regression approach to assess the effect of an R&D variable on the computed TFP growth rate. The regression coefficient on the R&D variable would provide an estimate of the social rate of return to R&D. The related studies tend to show high social rates of return to R&D, typically in a range of 20 to 40 % per year. We need to provide multiple equation dynamic system for productivity and innovation in Korean economy in state space form. A wide range of time series models, including the classical linear regression model, can be written and estimated as special cases of a state space specification. State space models have been applied in the econometrics literature to model unobserved variables like productivity. Estimation produces the following results. Considering the goodness of fit, we can see that the evidence is strongly in favor of the range $0.120{\sim}0.135$ for the elasticity of TFP to R&D stock in the period between 1970's and the early 2000's.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.84-91
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• 2002

A new composite control method for a carriage balancing single inverted pendulum system is proposed and applied to swing up the pendulum and to stabilize it under the state constraint. The target inverted pendulum system has an extremely limited length of the cart(below 16cm). The proposed swing-up controller comprises a sliding mode control algorithm and an optimal control algorithm based on two regions: the region near the inverted unstable equilibrium position and the rest of the state space including the downward stable equilibrium position. The sliding mode controller uses a switching control action to converge along the specified path(hyperplane) derived from energy equation from a state around the path to desired state(standing position). An optimal control method is also used to guarantee the stability at unstable equilibrium position. Compared with the reported controllers, it is simpler and easier to implement. Experimental results are given to show the effectiveness of this controller.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.2
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• pp.130-135
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• 2009

In recent years, researches on rotary inverted pendulum control systems have been significantly focused due their highly nonlinear dynamics and complicated geometric structures. This paper presents a novel control approach for such systems by means of similarity transformation theory. At first, we represent nonlinear system dynamics to the controllability-formed state space model including a time-varying parameter vector. We establish the state-feedback control configuration based on the transformed model and derive an adaptive control law for adjusting desired characteristic equation. Numerical analysis is achieved to evaluate our control method and demonstrate its superiority by comparing it to the traditional control strategy. Furthermore, real-time control experiment is carried out to test its practical reliability.