• 제어로봇시스템학회논문지
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• 제2권1호
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• pp.21-25
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• 1996

In this paper we suggest a general purpose RNN training algorithm which is derived on the optimal control concepts and variational methods. First, learning is regared as an optimal control problem, then using the variational methods we obtain optimal weights which are given by a two-point boundary-value problem. Finally, the modified gradient descent algorithm is applied to RNN for on-line training. This algorithm is intended to be used on learning complex dynamic mappings between time varing I/O data. It is useful for nonlinear control, identification, and signal processing application of RNN because its storage requirement is not high and on-line learning is possible. Simulation results for a nonlinear plant identification are illustrated.

• 설비공학논문집
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• 제17권2호
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• pp.140-146
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• 2005

The on-line optimal control algorithm for central heating system has been researched for minimizing energy consumption while maintaining the comfort of indoor thermal environment in terms of the environmental variables such as indoor heating load and outdoor temperature variation. This study has been done by using TRNSYS Program in order to analyze the central heating system. The optimal control algorithm shows good energy Performances in comparison with the conventional one.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.27.4-27
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• 2001

A stabilizing control method for linear systems with model uncertainties and hard input constraints is developed, which does not require on-line optimizations. This work is motivated by the constrained robust MPC(CRMPC) approach [3] which adopts the dual mode prediction strategy (i.e. free control moves and invariant set) and minimizes a worst case performance criterion. Based on the observation that, a feasible control sequence for a particular state can be found as a linear combination of feasible sequences for other states, we suggest a stabilizing control algorithm providing sub-optimal and feasible control sequences using pre-computed optimal sequences for some canonical states. The on-line computation of the proposed method reduces to simple matrix multiplication.

• 전기학회논문지
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• 제59권12호
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• pp.2131-2134
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• 2010

In this paper, the on-line system schemes for coordinated control system of multiple FACTS were presented to enhance the voltage stability around the metropolitan areas. In order to coordinated control system of FACTS devices, MFC on-line system calculates the optimal set point(Vref, Qrev) of FACTS devices using the coordinated control algorithm with real time network data which is transferred from SCADA/EMS system. If the system is unstable after contingencies, the new operation set-point of FACTS would be determined using bus sensitivity from tangent vector at voltage instability point. Otherwise, we would determine the new operation set-point of FACTS for considering economical operation, like as active power loss minimization using Optimal Power Flow algorithm. As the test, MFC(Multiple FACTS Coordinated control) on-line system will be installed in Korea power system.

• 한국자동차공학회논문집
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• 제9권1호
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• pp.112-121
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• 2001

In this paper, an engine-CVT integrated control algorithm is suggested by considering the powertrain loss, inertia torque and the CVT ratio response lag. The integrated control algorithm consists of (1) the optimal engine power calculation and (2) determining of the optimal throttle valve opening and the optimal CVT ratio. The optimal engine power is obtained by compensating the inertia torque due to the CVT ratio change and the powertrain loss that is calculated iteration procedure. In addition, an algorithm to compensate the effect of the CVT ratio response lag on the drive torque is suggested by the engine speed compensation causing the increased optimal CVT ratio. Simulation results show that the engine-CVT integrated control algorithm developed in this study makes it possible to obtain better engine operation on the optimal operating line, which results in the improved fuel economy while satisfying the driver's demand.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
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• pp.95-98
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• 2003

In this paper, an adaptive fuzzy neural control of unknown nonlinear systems based on the rapid learning algorithm is proposed for optimal parameterization. We combine the advantages of fuzzy control and neural network techniques to develop an adaptive fuzzy control system for updating nonlinear parameters of controller. The Fuzzy Neural Network(FNN), which is constructed by an equivalent four-layer connectionist network, is able to learn to control a process by updating the membership functions. The free parameters of the AFN controller are adjusted on-line according to the control law and adaptive law for the purpose of controlling the plant track a given trajectory and it's initial values are off-line preprocessing, In order to improve the convergence of the learning process, we propose a rapid learning algorithm which combines the error back-propagation algorithm with Aitken's $\delta$$\^$2/ algorithm. The heart of this approach ls to reduce the computational burden during the FNN learning process and to improve convergence speed. The simulation results for nonlinear plant demonstrate the control effectiveness of the proposed system for optimal parameterization.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집B
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• pp.546-551
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• 2001

In this paper, an algorithm to improve the optimal engine operation is suggested by increasing the CVT shift speed. By rearranging the CVT shift dynamic equation, it is found that the CVT shift speed depends on the line pressure as well as the primary pressure. Based on the shift dynamics, an algorithm to accomplish a faster shift speed is presented by increasing the line pressure. In order to apply the algorithm, dynamic models of the line pressure control valve and the ratio control valve are obtained by considering the CVT shift dynamics and model based controllers are designed. It is found from the simulation results that fuel economy can be improved by 2% in spite of the increased hydraulic loss due to the increased line pressure.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.977-979
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• 1996

This paper presents an algorithm to control the undesirable sway of a suspended load in the crane system that has a trade-off between positioning the load and suppressing the sway of the load. The aim is to transport the load to a specified place with small sway angle as quickly as possible. Dynamic model is based on a simple pendulum driven by a velocity drive that is mostly used for actuating a trolley in industry. Proposed algorithm is composed of two parts : one is a off-line optimal trajectory generator, the other on-line tracking control. The former produces optimal trajectories minimizing energy under the speed constraint of velocity drive. The latter controls outputs to track the generated trajectories. Digital simulations and experiments are performed on a pilot crane to demonstrate the performance of the proposed control algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.279-282
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• 1995

In this paper, a moving horizon control algorithm, which can be applied for a wide class of nonlinear systems with control and state constraints, is considered. In a neighborhood of the origin, a linear feedback controller is applied. Outside this neighborhood, a moving horizon control law is applied. The time taken to solve an optimal control problem is considered in the algorithm so that the proposed control law can be applied as an on-line controller.

• 대한전기학회논문지
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• 제43권4호
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• pp.586-593
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• 1994

This paper suggests the algorithm for on-line efficiency control of permancent magnet synchronous motors driving the electric vehicles. The existance of unigue d-axis current is verified, which generates the maximum efficiency at operating points of motor. Using the Fibonacci search method, d-axis current converges to the minimization of inverter input power, and to prevent the variation of motor speed in process of the efficiency control, the voltage decoupled control strategy is introduced. Through the experiments, the effects of an efficiency control algorithm are verified.