• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.485-492
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• 1998

Most forecasting models often fail to produce appropriate forecasts because we build a model based on the assumption of the data being generated from the only one stochastic process. However, in many real problems, the time series data are generated from one stochastic process for a while and then abruptly undergo certain structural changes. In this paper, we assume the basic underlying process is the simple state-space model with random level and deterministic drift but interrupted by three types of exogenous shocks: level shift, drift change, outlier. A Bayesian procedure to detect, estimate and adapt to the structural changes is developed and compared with simple, double and adaptive exponential smoothing using simulated data and the U.S. leading composite index.

• Industrial Engineering and Management Systems
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• v.3 no.1
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• pp.1-11
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• 2004

This paper proposes a new algorithm for determining an optimal control input for production systems. In many production systems, completion time should be planned within the due dates by taking into account precedence constraints and processing times. To solve this problem, the max-plus algebra is an effective approach. The max-plus algebra is an algebraic system in which the max operation is addition and the plus operation is multiplication, and similar operation rules to conventional algebra are followed. Utilizing the max-plus algebra, constraints of the system are expressed in an analogous way to the state-space description in modern control theory. Nevertheless, the formulation of a system is currently performed manually, which is very inefficient when applied to practical systems. Hence, in this paper, we propose a new algorithm for deriving a state-space description and determining an optimal control input with several constraint matrices and parameter vectors. Furthermore, the effectiveness of this proposed algorithm is verified through execution examples.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.191-196
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• 2005

Genetic networks are a key to unraveling dynamic properties of biological processes and regulation of genes plays an essential role in dynamic behavior of the genetic networks. A popular characterization of regulation of the gene is a kinetic model. However, many kinetic parameters in the genetic regulation have not been available. To overcome this difficulty, in this report, state-space approach to modeling gene regulation is presented. Second-order systems are used to characterize gene regulation. Interpretation of coefficients in the second order systems as resistance, capacitance and inductance is studied. The mathematical methods for transient response analysis of gene regulation to external perturbation are investigated. Criterion for classifying gene into three categories: underdamped, overdamped and critical damped is discussed. The proposed models are applied to yeast cell cycle gene expression data.

• 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 Mechanical Science and Technology
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• v.19 no.2
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• pp.618-624
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• 2005

We present a new state-space approach to construct a dynamic output feedback controller which stabilizes a class of linear time invariant systems. All the states of the given system are not measurable and only the output is used to design the stabilizing control law. In the design scheme, however, we first assume that the given system can be stabilized by a feedback law composed of the output and its derivatives of a certain order. Beginning with this assumption, we systematically construct a dynamic system which removes the need of the derivatives. The main advantage of the proposed controller is regarding the controller order, which may be smaller than that of conventional output feedback controller. Using a simple numerical example, it is shown that the order of the proposed controller is indeed smaller than that of reduced-order observer based output feedback controller.

• Smart Structures and Systems
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• v.18 no.4
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• pp.707-731
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• 2016

A unified mathematical model of the equations of generalized magneto-thermoelasticty based on fractional derivative heat transfer for isotropic perfect conducting media is given. Some essential theorems on the linear coupled and generalized theories of thermoelasticity e.g., the Lord- Shulman (LS) theory, Green-Lindsay (GL) theory and the coupled theory (CTE) as well as dual-phase-lag (DPL) heat conduction law are established. Laplace transform techniques are used. The method of the matrix exponential which constitutes the basis of the state-space approach of modern theory is applied to the non-dimensional equations. The resulting formulation is applied to a variety of one-dimensional problems. The solutions to a thermal shock problem and to a problem of a layer media are obtained in the present of a transverse uniform magnetic field. According to the numerical results and its graphs, conclusion about the new model has been constructed. The effects of the fractional derivative parameter on thermoelastic fields for different theories are discussed.

• Proceedings of the KIEE Conference
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• 1984.07a
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• pp.38-40
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• 1984

• Journal of Astronomy and Space Sciences
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• v.30 no.4
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• pp.279-290
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• 2013

Due to the continuous space development by mankind, the number of space objects including space debris in orbits around the Earth has increased, and accordingly, difficulties of space development and activities are expected in the near future. In this study, among the stages for space debris removal, the implementation of a vision-based approach technique for approaching space debris from a far-range rendezvous state to a proximity state, and the ground test performance results were described. For the vision-based object tracking, the CAM-shift algorithm with high speed and strong performance, and the Kalman filter were combined and utilized. For measuring the distance to a tracking object, a stereo camera was used. For the construction of a low-cost space environment simulation test bed, a sun simulator was used, and in the case of the platform for approaching, a two-dimensional mobile robot was used. The tracking status was examined while changing the position of the sun simulator, and the results indicated that the CAM-shift showed a tracking rate of about 87% and the relative distance could be measured down to 0.9 m. In addition, considerations for future space environment simulation tests were proposed.

• Structural Engineering and Mechanics
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• v.23 no.1
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• pp.97-113
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• 2006

A simply supported hybrid plate consisting of top and bottom functionally graded elastic layers and an intermediate actuating or sensing homogeneous piezoelectric layer is investigated by an elasticity (piezoelasticity) method, which is based on state space formulations. The general spring layer model is adopted to consider the effect of bonding adhesives between the piezoelectric layer and the two functionally graded ones. The two functionally graded layers are inhomogeneous along the thickness direction, which are approached by laminate models. The effect of interlaminar bonding imperfections on the static bending and free vibration of the smart plate is discussed in the numerical examples.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.35-43
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• 2001

In this paper, we propose a design method for GBSB (generalized brain-state-in-a-box) based associative memories. Based on the theoretical investigation about the properties of GBSB, we parameterize the solution space utilizing the limited number of parameters sufficient to represent the solution space and appropriate to be searched. Next we formulate the problem of finding a GBSB that can store the given pattern as stable states in the form of constrained optimization problems. Finally, we transform the constrained optimization problem into a SDP(semidefinite program), which can be solved by recently developed interior point methods. The applicability of the proposed method is illustrated via design examples.