• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.9
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• pp.881-888
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• 2004

Control algorithms for a dual source chiller air conditioning system were developed. These are control algorithms for the supply air temperature control, the supply header chilled water temperature control, the chiller chilled water temperature control, and the cooling tower water temperature control. These algorithms were analyzed by using a dynamic simulation program. Simulation results showed the energy savings and the satisfactory controls of an absorption and centrifugal chiller air conditioning system. Therefore, control algorithms developed for this study may effectively be used for the improved controls of the dual source chiller air conditioning system.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.447-452
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• 2015

This paper considers a two-stage make-to-stock production system. The first stage produces a single-component and the second stage produces a make-to-stock product using components. In addition to internal demands, the first stage faces external demands with the option of accepting or rejecting. To ration component inventory, the manufacturer adopts a static rule. This paper analyzes the production controls at both facilities that maximizes the manufacturer's profit. Using the Markov decision process model, we characterize the optimal production policy by two monotonic switching curves.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.175-178
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• 2002

A number of controlled selection methods, which have some advantages for practical surveys in considering controls beyond stratification, have developed throughout the last half-century. With respect to the optimization of sampling plan, it is obvious that we may use optimal controlled selection in preference to satisfactory controlled selection. However, there are currently certain restrictions on the employment of optimal controlled selection. We present further research to improve an algorithm for optimal controlled selection and to develop standard software.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.4
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• pp.15-26
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• 1998

Full car model is needed for investigating as a entire dynamics of vehicle. In this study, 7DOF of full car model's dynamics is selected. This paper proposes the output feedback controller based on optimal control theory. Input data and output data from the optimal controller are used for neural network system identification of the suspension system. To do system identification, neural network which has robustness against nonlinearities and disturbances is adapted. This study uses back-propagation algorithm to train a multil-layer neural network. After obtaining a neural network model of a suspension system, a neuro-controller is designed. Neuro-controller controls suspension system with off-line learning method and multistep ahead prediction model based on the neural network model and a neuro-controller. The optimal controller and the neuro-controller are designed and then, both performances are compared through. For simulation, sinusoidal and rectangular virtual bumps are selected.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1736-1740
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• 2003

POSCO Kwang-Yang Works #2 Cold Rolling Mill RCL has the main hydraulic system that controlled on/off control method. In the aspect of the consumption of electrical energy this system has some problem. So, we present a continuous control method instead of on/off control method that controls the pressure of main hydraulic system with saving the electric energy.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.464-469
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• 1987

The Kalman filter is an optimal linear estimator that has been an active research topic for the past three decades. The scheme has become the milestone of modern filtering, and it is applied to many areas including navigations and controls of free vehicle. The Kalman filter technique is matured. But some problems are still remained to be resolved. The prevention of divergence induced by digital implementation, nonoptimal application for nonlinear system, and application to non-Gaussian processes are some of the problems. This paper surveys the problems. The square root filtering is suggested to prevent the divergence. The extended Kalman filter is used for nonlinear systems. And, many other approaches to Kalman-like optimal estimators are also investigated.

• Journal of the Korean Mathematical Society
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• v.34 no.3
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• pp.553-567
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• 1997

This paper is concerned with the control problem $$ \dot{x}(t) = F(x) + u(t)G(x), t \in [0,T], x(0) = 0, $$ where F and G are smooth vector fields on $R^n$, and the admissible controls u satisfy the constraint $$\mid$u(t)$\mid$ \leq 1$. We provide the sufficient condition that the bang-bang trajectories having different switching orders intersect.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.440-444
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• 1998

In this paper, we consider numerical solution of a H-J-B (Hamilton-Jacobi-Bellman) equation of elliptic type arising from the stochastic control problem. For the numerical solution of the equation, we take an approach involving contraction mapping and finite difference approximation. We choose the It(equation omitted) type stochastic differential equation as the dynamic system concerned. The numerical method of solution is validated computationally by using the constructed test case. Map of optimal controls is obtained through the numerical solution process of the equation. We also show how the method applies by taking a simple example of nonlinear spacecraft control.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2001.05a
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• pp.225-230
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• 2001

In this paper, a method for optimal design of PID controller using the immune algorithm(IA) has been proposed to improve the stability of A.C.-D.C. power system. The process of this study is composed of formulation of basic controls on HVDC transmission system, mathematical model preparation for stability analysis, and supplementary signal control by an optimal PID controller using the IA. The dynamic property was verified through computer simulations regarding transient stability.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.99-121
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• 2017

Standard makers in both private and public sectors have been increasingly mandating security standards upon organizations to protect organizational digital assets. A major issue in security standardization is that standards often cannot regulate all possible security efforts by the standard maker because some efforts are unverifiable by nature. This paper studies from an analytical perspective how a standard maker should design the standard using a verifiable security control in the presence of another related unverifiable one. We compare it with two benchmark standards; $na{\ddot{i}}ve$-standard which refers to the standard maker who ignores the existence of the unverifiable control, and complete-information standard which refers to the maker sets standards on both controls. Optimal standard and benchmark standard depend critically on how the two controls are configured. Under parallel configuration, the existence of the unverifiable control induces the policy maker to set a higher standard (the complete-information standard is optimal); under serial configuration, a lower standard is applied (neither benchmark works). Under best-shot configuration and if the verifiable control is more cost-efficient, the existence of the unverifiable control has no impact on the optimal standard (the $na{\ddot{i}}ve$ standard is optimal).