• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.325-328
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• 1997

In this paper the modeling and control of a twin roll strip caster is investigated. Mathematical models for the strip casting process are obtained by analyzing five critical areas such that the molten steel level in the pool, solidification process, roll separating force and torque, roll dynamics including hydraulic actuators, and roll drive system. A two-level control strategy is proposed. At lower level, three local subsystems are independently feedback-controlled by suitable local controllers which perform well to the behaviors of each subsystem. They are a variable structure control of the molten steel level in the pool, an adaptive predictive control of the roll gap which is directly related to the strip thickness, and an $H^{\infty}$ control of the roll drive system. At higher level, all reference signals to the lower level subsystems are generated by an optimal controller in the perspective of regulating the strip thickness and roll separating force. Simulations are provided..

• International Journal of Contents
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• v.2 no.2
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• pp.10-16
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• 2006

In this paper, we propose a predictive resource metric region (RMR) based radio resource metric estimation (RRME) mechanism, which utilizes a resource metric mapping function (RMMF), both of which permit efficient inter-working between the physical layer and higher layers for envisaging multimedia service applications over a CDMA communication system platform. The RMR can provide the acceptable resource region where QoS and acceptable link quality can be guaranteed with an achievable resource margin to be utilized in terms of capacity margin, the degree of confidence (DCL) of user, second-order statistics of Eb/Io. With predicted capacity margin and variance, DCL can deliver decision parameters with which an adaptive QoS based admission control can perform well taking capacity and resource availability into account in a dynamic and predictive manner. Combined with advanced techniques such as adaptive modulation or rate control and power control, the proposed mechanism can adjust the conventional stringent link quality information efficiently, and deliver accurate information of the resource availability. Thus, these can guarantee the maximization of resource utilization of multimedia service applications.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.212-216
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• 2003

The performance of active power filter depends on the inverter characteristic, the control method, and the accuracy of reference signal generator. The accuracy of reference generator is the most critical item to determine the performance of active power filter. This paper introduces a novel reference signal generator composed of improved adaptive predictive filter. The performance of proposed reference signal generator was verified by means of simulation with MATLAB. The simulation result confirm that the proposed reference signal generator can be utilized for the active power filter.

• Nuclear Engineering and Technology
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• v.27 no.6
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• pp.833-844
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• 1995

In self-tuning predictive control algorithm for steam generator is presented. The control algorithm is derived by suitably modifying the generalized predictive control algorithm. The main feature of the unposed method relies on considering the measurable disturbance and a simple adaptive scheme for obtaining the controller gain when the parameters of the plant are unknown. This feature makes the proposed approach particularly appealing for water level control of steam generator when measurable disturbance is used. In order to evaluate the performance of the proposed algorithm, computer simulations are done for an PWR steam generator model. Simulation result show satisfactory performances against load variations and steam flow rate estimation errors. It can be also observed that the proposed algorithm exhibit better responses than a conventional PI controller.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.5
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• pp.120-127
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• 2009

An electric furnace, inside which desired temperatures are kept constant by generating heat, is known to be a difficult system to control and model exactly because system parameters and response delay time vary as the temperature and position are changed. In this study the heating system of ceramic drying furnaces with time-varying parameters is mathematically modeled as a second order system and control parameters are estimated by using a RIV (Recursive Instrumental-Variable) method. A modified bang-bang control with magnitude tuning is proposed in the time optimal temperature control of ceramic drying electric furnaces and its performance is experimentally verified. It is proven that temperature tracking of adaptive time optimal control using a second order model is more stable than the GPCEW (Generalized Predictive Control with Exponential Weight) and rapidly settles down by pre-estimation of the system parameters.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.168-172
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• 1994

This paper shows that the GPC with exponential weighting(GPCEW) can be applied to Electric furnace system which has large time delay. Stability of GPCEW can be guarantee from monotonically non-increasing property of Riccati difference equation. We show that the performance of GPCEW versus GPC and auto-tuning PID control is better than that of GPC or atito-tuning PID.

• Journal of Power Electronics
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• v.11 no.5
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• pp.751-758
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• 2011

This paper presents an effective robust predictive control scheme for the active power filter (APF) using a smith-predictor based current regulator, which show superior features when compared to proportional-integral (PI) controllers in terms of an enhanced closed-loop bandwidth and an improved current tracking accuracy. A moving average filter (MAF) is implemented using a field programmable gate array (FPGA) for signal pre-processing to eliminate the switching ripple contamination. An adaptive linear neural network (ADALINE) is used for individual harmonic estimation to achieve selective compensation purpose. The effectiveness and validity of the devised control algorithm are confirmed by extensive simulation and experimental results.

• Journal of Integrative Natural Science
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• v.5 no.3
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• pp.182-185
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• 2012

In this paper, For 4th generation wireless communication systems, we propose a method to predict FH patterns in FH-OFDMA systems. OFDM is recognized as a promising modulation technique. Multi-user allocation in OFDM system can use FH that provides the spectrum-spread techniques. If one can generate more predictable FH sequences, then performance of the system can be easily improved. Current random FH and simple adaptive FH methods, however, are not considering predicting FH sequences. In this paper we show that the sampling of the wireless faded signal is not realized as a certain probability nature. With this regard, the proposed predictive FH allocation method is designed to embed the unknown probability models. Simulation study shows that the predictive FH method is more accurately predict FH sequences than the random or simple adaptive FH methods. We will further improve this proposed method to apply QoS control and MAC function development in OFDMA based wireless physical structures, especially maritime wireless data communications.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.43-50
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• 1997

Refuse incineration plant operations involve many kinds of uncertain factors, such as the variable physical properties of refuse as fuel and the complexity of the burning phenomenon. This makes it very dificult to apply conventional control methods to the combustion control of the refuse. So most of the refuse incineration plant are operated by operators. In this paper, an multi-variable fuzzy model predictive controller is proposed for the combustion control of the re:fuse. Adaptive network based fuzzy inference system is used for modeling of the refuse incineration plant and multi-variable fuzzy model predictive controller is designed based on the identified fuzzy model. And computer simulation was carried out to evaluate performance of the proposed controller.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.330-335
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• 1998

In this paper the robust vector control method of induction motor for the purpose of improving the system performance deterioration caused by parameter variations is proposed. The estimations of the stator current and the rotor flux are obtained by the full order state observer with corrective prediction error feedback. and the adaptive scheme is constructed to estimate the rotor speed with the error signal between real and estimation value of the stator current. Adaptive sliding observer based on the variable structure control is applied to parameter identification. Consequently predictive current control and speed sensorless vector control can be obtained simultaneously regardless of the parameter variations.