• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1152-1157
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• 2005

This paper is concerned with the construction of an improved sliding mode control for the active suspension system of a one-wheel car model subject to the excitation from a road profile. The active control is composed of the equivalent and the switching controls where an improved sliding surface is proposed. The active control force is generated by operating a pneumatic actuator due to the control signal that constructed by measuring the state variables of the car model and by estimating the excitation from the road profile using the VSS observer. The experimental result indicates that the proposed active suspension system is relatively effective in the vibration suppression of the car model.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.10
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• pp.509-515
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• 2000

This paper addresses a damping control strategy of Static Synchronous Series Compensator(SSSC) and analysis model for stability study. The effect of injected voltage source generated by SSSC is modelled as equivalent load. This model is thought to be reasonable for the stability study because the dynamics of SSSC is very fast compared with that of power system. Damping controller of SSSC is based on Transient Energy Function method. The proposed control strategy is insensitive to the operating conditions like power flow level because control law depends on the phase angles. The proposed analysis model and control strategy was confirmed by WSCC 9 bus system and two area system. Especially, the robustness of proposed control strategy is demonstrated with respect to multiple operating conditions in two area system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.5-75
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• 2001

In this paper, we study design of a ILQ(Inverse Linear Quadratic optimal control) looper control system for hot strip mills. The looper which is placed between stands plays an important role in controlling strip width by regulating strip tension variation generated from the velocity difference of main work rolls. A Looper servo controller is designed by ILQ control theory which is an inverse problem of LQ(Linear Quadratic optimal control) control. The mathematical model for looper system is obtained by Taylor´s linearization of nonlinear differential equations. Then we designed linear controller for linearization model by using the ILQ control algorithm. Thereafter this controller is applied to the nonlinear model for model identification. As a result, we show the controller´s robustness for the model error, external disturbance and sensor noise.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.329-334
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• 2010

This paper presents the design of a neural network based adaptive control for missile. Acceleration of missile by tail fin control cannot be controllable by DMI (Dynamic Model Inversion) directly because it is non-minimum phase system. To avoid the non-minimum phase system, dynamic model inversion is applied with output-redefinition method. In order to evaluate performance of the suggested controllers we selected the three cases such as control surface fail, control surface loss and wing loss for model uncertainty. The corresponding aerodynamic databases to the failure cases were calculated by using the Missile DATACOM. Using a high fidelity 6DOF simulation program of the missile the performance was evaluates.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.268-272
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• 2007

These days many scientists make studies of feedback control system for stability on non-linear state and for the maneuver of flying objects. These feedback control systems have to satisfy trajectory condition and angular conditions, that is to say, controllability and stability simultaneously to achieve mission. In this paper, a design methods using model based control system which consists of spiral predictive model, Q-function included into generalized-work function is shown. It is made a clear that the proposed algorithm using SPM maneuvers for controllability and stability at the same time is successful in attaining our purpose. The feature of the proposed algorithm is illustrated by simulation results. As a conclusion, the proposed algorithm is useful for the control of moving objects.

• Journal of the Korean Institute of Telematics and Electronics
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• v.18 no.3
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• pp.35-41
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• 1981

In this paper, the application of model reference adaptive control theory to the D.C motor speed control using the microprocessor is studied. It is shown that with the use of an adaptive control algorithm the error between output of the motor and the reference model, which is approximated to first order, can be conve to zero. By computer simulation and the practical implementation with the microprocessor M 6800, can be concluded that the adaptive control system adapts well to the rapid change of the load and reference inputs.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.234-234
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• 1999

The aim of this paper is to suggest a design method of the optimal model following control system using genetic algorithm (GA). This control system is designed by applying GA with reference model to the optimal determination of weighting matrices Q, R that are given by LQ regulator problem. The method to do this is that all the diagonal elements of weighting matrices are optimized simultaneously by GA, in the search domain selected adequately. And we design the model following control system to boi1er-turbine equipment by the proposed method. The model following control system designed by this method has the better command tracking performance than that of the control system designed by the trial-and-error method. The effectiveness of this control system is verified by computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1076-1080
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• 2015

An inventory control system was developed for a distribution system consisting of a single multiproduct warehouse serving a set of customers and purchasing products from multiple vendors. Purchase orders requesting multiple products are delivered to the warehouse in a process. The receipt of customer orders by the warehouse proceeded in order intervals and in order quantities that are subject to random fluctuations. The objective of warehouse operation is to minimize the total cost while maintaining inventory levels within the warehouse capacity by adjusting the purchase order intervals and quantities. An adaptive model predictive control algorithm was developed using a periodic square wave model to represent the material flows. The adaptive concept incorporated a stabilized minimum variance control-type input calculation coupled with input/output stream parameter predictions. The effectiveness of the scheme was demonstrated using simulations.

• Proceedings of the Korea Society for Simulation Conference
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• 2004.05a
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• pp.109-117
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• 2004

In this paper, we consider the aortic sinus baroreceptor, which is the most representative baroreceptor sensing the variance of pressure in the cardiovascular system, and propose heart activity control model to observe the effect of delay time in heart period and stroke volume under the regulation of baroreflex in the aortic sinus. The proposed heart activity baroreflex regulation model contains electric circuit sub-model. We constituted the time delay sub-model to observe sensitivity of heart activity baroreflex regulation model by using the variable value to represent the control signal transmission time from the output of baroreflex regulation model to efferent nerve through central nervous system. The simulation object of this model is to observe variability of the cardiovascular system by variable value in time delay sub-model. As simulation results, we observe three patterns of the cardiovascular system variability by the time delay, First, if the time delay over 2.5 second, aortic pressure and stroke volume and heart rate is observed nonperiodically and observed. Finally, if time delay under 0.1 second, then heart rate and aortic pressure-heart rate trajectory is maintained in stable state.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1449-1454
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• 2003

For many industrial processes there are good static models used for process design and steady state operation. By using system identification techniques, it is possible to obtain black-box models with reasonable complexity that describe the system well in specific operating conditions [1]. But black-box models using inductive modeling(IM) is not suitable for model based control because they are only valid for specific operating conditions. Thus we need to use deductive modeling(DM) for a wide operating range. Furthermore, deductive modeling is several merits: First, the model is possible to be modularized. Second, we can increase and decrease the model complexity. Finally, we are able to use model for plant design. Power plant must be able to operate well at dramatic load change and consider safety and efficiency. This paper proposes a simplified nonlinear model of an industrial boiler, one of component parts of a power plant, by DM method and applies optimal control to the model.