• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.91-106
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• 1996

Control Variate (CV) is very useful technique for variance reduction in a wide class of queueing network simulations. However, the loss in variance reduction caused by the estimation of the optimum control coefficients is an increasing function of the number of control variables. Therefore, in some situations, it is required to select an optimal set of control variables to maximize the variance reduction . In this paper, we develop the Adaptive Control Variates (ACV) method which selects an optimal set of control variates during the simulation adatively. ACV is useful to maximize the simulation efficiency when we need iterated simulations to find an optimal solution. One such an example is the Simulated Annealing (SA) because, in SA algorithm, we have to repeat in calculating the objective function values at each temperature, The ACV can also be applied to the queueing network optimization problems to find an optimal input parameters (such as service rates) to maximize the throughput rate with a certain cost constraint.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.145-147
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• 1993

This paper described an optimal control technique for position control of an inverter-fed PMSM drive. A control system of PM machine for position, speed and current control based on optimal sliding mode control system is discussed. This is an effective means to keep a system insensitive to parameter variation, disturbance and chattering reduction. The main purpose of the control is to improve the dynamic response of the PMSM with the load of the inertial plant. The optimal sliding mode control strategy is analyzed and the performance is investigated by the computer simulation using actual parameters of a drive system, Simulation results are given and discussed.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.828-833
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• 2003

Rigid plate elastically supported at the edges is modeled and the performance of the optimal vibration control under sinusoidal excitation is tested. The controller based on the linear quadratic regulator with output feedback is designed to control the multi-degree of freedom vibration. Relative weighting parameters are considered as design constraints to determine the limitation of maximum control force and state parameters. Control force calculated by proportional output feedback of the displacement and velocity is used to suppress the vibration induced by the sinusoidal external force. The active vibration control of vibrating plate by the LQR controller is examined through the numerical simulations that show the effectiveness of optimal control scheme on the three degrees of freedom structure.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.538-541
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• 1995

In steel works, reheating furnace is an essential part of a rod mill plant and it treats various types of billets continuously. Although getting an optimal setting for a single billet is simple, control setting for whole groups of billets is a difficult task. In this work, we studied a detail mathematical model and optimal control setting of reheating furnace. As the mathematical model of each billet is a partial differential equation, on-line control is almost impossible for the whole billets charged into the furnace. Therefore, we tried to provide a guideline for optimal setting value of the roof(index) temperature for the target billets which account for about 20% of the charged billets.

• Smart Structures and Systems
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• v.15 no.5
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• pp.1177-1202
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• 2015

The present paper is concerned with the optimal control and/or design of symmetric and antisymmetric composite laminate with two piezoelectric layers bonded to the opposite surfaces of the laminate, and placed symmetrically with respect to the middle plane. For the optimal control problem, Liapunov-Bellman theory is used to minimize the dynamic response of the laminate. The dynamic response of the laminate comprises a weight sum of the control objective (the total vibrational energy) and a penalty functional including the control force. Simultaneously with the active control, thicknesses and the orientation angles of layers are taken as design variables to achieve optimum design. The formulation is based on various plate theories for various boundary conditions. Explicit solutions for the control function and controlled deflections are obtained in forms of double series. Numerical results are given to demonstrate the effectiveness of the proposed control and design mechanism, and to investigate the effects of various laminate parameters on the control and design process.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.9
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• pp.2142-2153
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• 1995

A digital preview controller using optimal LQ control theory is suggested for tandem cold mills to achieve a remarkable improvement of the thickness accuracy. Optimal preview control system is constructed for each rolling stand of tandem cold mills for which the blocked noninteracting control is carried out, and it is compared with the optimal LQ control system which has only feedback control. And in the cases that all/some of disturbance inputs are previewable, full and partial preview controllers are designed, and their performance effects are compared and discussed. The simulation results show that the performance of tandem cold mills can be improved largely through partial preview control.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.160-170
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• 2008

Temperature control of an enclosed thermal system which has many applications including Rapid Thermal Processing (RTP) of semiconductor wafers showed an input-constraint violation for nonlinear controllers due to inherent strong coupling between the elements [1]. In this paper, a constrained nonlinear optimal control design is developed, which accommodates input constraints using the linear algebraic equivalence of the nonlinear controllers, for the temperature control of an enclosed thermal process. First, it will be shown that design of nonlinear controllers is equivalent to solving a set of linear algebraic equations-the linear algebraic equivalence of nonlinear controllers (LAENC). Then an input-constrained nonlinear optimal controller is designed based on that LAENC using the constrained linear least squares method. Through numerical simulations, it is demonstrated that the proposed controller achieves the equivalent performances to the classical nonlinear controllers with less total energy consumption. Moreover, it generates the practical control solution, in other words, control solutions do not violate the input-constraints.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.349-352
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• 2005

The energy management of an HEV using optimal control and global optimization is thought to be closest to the best operation of the system. However, there are some controversies on the ways of defining the optimization problems and constituting the optimal control simulators. Here, we presented a simulator which adopts the concept of equivalent fuel economy and leads the vehicle to run in a more efficient way. In order to realize the optimal operation of the HEV and check the validity of the control logics, we also developed a forward-facing simulator. The simulator was developed with the Cruise and MATLAB co-simulation interface. Especially, neural network controller was used for the hybrid control module in the simulator. With the simulator, the optimal operation could be converted into hybrid control rules and the validity of the operation was verified.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.659-664
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• 2000

Fuel-consumption and catalyst-out emissions of a parallel hybrid electric vehicle are affected by operating region of an engine. In many researches, It is generally known that it is profitable in fuel- consumption to operate engine in OOL(Optimal Operating Line). We established the mathematical model of a parallel hybrid electric vehicle, which is linear time-invariant. To operate an engine in OOL, we applied RHC(Receding Horizon Control) to the driving control of a parallel hybrid electric vehicle. And it is known that the RHC has advantages such as good tracking performance under state and control constraints. This RHC is obtained by using linear matrix inequality (LMI) optimization. In this paper, there are three main topics. First, without state and control constraints, the optimal tracking of OOL was simulated. Second, with state and control constraints by engine and motor performances, the optimal tracking of OOL was simulated. In the last, we studied on the optimal gear ratio. That is to say, we combined the RHC and the iterative simulation to extract the optimal gear ratio. In this simulation, the vehicle is commanded to track the reference vehicle trajectory and the engine is operated in the optimal operating region which is made by the state constraints.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1951-1956
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• 2003

It is known that HIV (Human Immunodeficiency Virus) infection, which causes AIDS after some latent period, is a dynamic process that can be modeled mathematically. Effects of available anti-viral drugs, which prevent HIV from infecting healthy cells, can also be included in the model. In this paper we illustrate control theory can be applied to a model of HIV infection. In particular, the drug dose is regarded as control input and the goal is to excite an immune response so that the symptom of infected patient should not be developed into AIDS. Finite horizon optimal control is employed to obtain the optimal schedule of drug dose since the model is highly nonlinear and we want maximum performance for enhancing the immune response. From the simulation studies, we find that gradual reduction of drug dose is important for the optimality. We also demonstrate the obtained open-loop optimal control is vulnerable to parameter variation of the model and measurement noise. To overcome this difficulty, we finally present nonlinear receding horizon control to incorporate feedback in the drug treatment.