• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.164-168
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• 1988

This paper utilizes an optimal control law for the accurate tracking servo system design. The devivation of a simple control law implementing microprocessor is made to minimize position and speed error of the controller. The 16 bit microprocessor receives command angular position and calculate the control algorithm for accurate tracking and provides control system gain scheduling to achieve very short settling time. Simulation results and some experimental results of the position controlled tracking using 4.5Kw DC servo motor are shown.

• ETRI Journal
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• 제6권2호
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• pp.3-9
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• 1984

This paper proposes an optimal control scheme for shaft position control using microcomputer-based state-variable feedback. In this scheme a performance index was set up in order to ruduce the overshoot and improve the steady- state response speed, and the time-variant system parameters were identified in real time for optimal control. As a result of experiment, the over-shoot was not occured and the response speed was improved 2. 9 times about proportional control. This scheme improves the performance against the variation of load and sampling time, and adding the integral control in this scheme can reduce the steady-state error without any change in response time.

• Journal of Power Electronics
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• 제17권2호
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• pp.323-333
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• 2017

This paper proposes a model-based optimal control algorithm for the clamp switch of a zero-voltage switching (ZVS) bidirectional DC-DC converter. The bidirectional DC-DC converter (BDC) can accomplish the ZVS operation using the clamp switch. The minimum current for the ZVS operation is maintained, and the inductor current is separated from the input and output voltages by the clamp switch in this topology. The clamp switch can decrease the inductor current ripple, switching loss, and conduction loss of the system. Therefore, the optimal control of the clamp switch is significant to improve the efficiency of the system. This paper proposes a model-based optimal control algorithm using phase shift in a micro-controller unit. The proposed control algorithm is demonstrated by the results of PSIM simulations and an experiment conducted in a 1-kW ZVS BDC system.

• 한국소음진동공학회논문집
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• 제22권7호
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• pp.650-658
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• 2012

This paper proposes a high performance position controller for a driving system using a time optimal controller which has been widely used to control driving systems to achieve desired reference position or velocity in a minimum response time. The main purpose of this research lies in an improvement of transient response performance rather than that of steady-state response in comparison with other control strategies. In order to refine the scheme of time optimal control, Lyapunov stability proofs are incorporated in a controller of standard second order system model. This scheme is applied to the control of a driving system. In view of the simulation and experiment results, the standard second order system model exhibits better minimum-time control performance and robustness than double integral system model does.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 A
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• pp.382-384
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• 1996

This paper introduces the controller development of booster multi-pump system with constantly estimated control algorithm. Through analyzing by the experiment of optimal pressure with a certain flow rate. The larger pressure processing apparatus in microprocessor makes optimal water-supplying. This method is implemented with the only pure control algorithm without any other mechanical or circuitry apparatus. Also, Pump's life is lengthened by exchanging simple on, off and rotational inverter control. Optimal condition for pump is adjusted by the inverter control, and compact control panel helps the booster system install in real field.

• 동력기계공학회지
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• 제17권4호
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• pp.120-130
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• 2013

An adaptive PID sliding mode controller is proposed for the position control of electro-hydrostatic actuator(EHA) systems with system uncertainties and saturation in the motor. An EHA prototype is developed and system modeling and parameter identification are executed. Then, adaptive PID sliding mode controller and optimal anti-windup PID controller are designed and the performance and robustness of the two control systems are compared by experiment. It was found that the adaptive PID sliding mode control system has better performance and is more robust to system uncertainties than the optimal anti-windup PID control system.

• 한국멀티미디어학회논문지
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• 제18권11호
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• pp.1375-1382
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• 2015

This paper aims to introduce the numerical methods for solving the optimal control theory to model bufferbloat problem. Mathematical tools are useful to provide insight for system engineers and users to understand better about what we are facing right now while experiment in a large-scale testbed can encourage us to implement in realistic scenario. In this paper, we introduce a survey of the numerical methods for solving the optimal control problem. We propose the dynamic optimization sweeping algorithm for optimal control of the active queue management. Simulation results in network simulator ns2 demonstrate that our proposed algorithm can obtain the stability faster than the others while still maintain a short queue length (≈10 packets) and low delay experience for arriving packets (0.4 seconds).

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.395-396
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• 2006

This paper presents the optimal design of Robot-Arm part use Design of Experiment(DOE). The DOE(Design of Experiment)was conducted to find out main effect factors for design of Robot-Arm part. In this design of Robot-Arm, 5 control factors include numbers of 4 level are selected and we make out L16 orthogonal array. Using this orthogonal array, find out optimal value and main effect factors of object function for design of Robot-Arm part by 16 times of test. We evidence this optimal value by using CATIA V5 Analysis.

• Bulletin of the Korean Chemical Society
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• 제24권6호
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• pp.744-750
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• 2003

In quantum dynamics of many-body systems, to identify the Hamiltonian becomes more difficult very rapidly as the number of degrees of freedom increases. In order to simplify the dynamics and to deduce dynamically relevant Hamiltonian information, it is desirable to control the dynamics to lie within a reduced space. With a judicious choice for the cost functional, the closed loop optimal control experiments can be manipulated efficiently to steer the dynamics to lie within a subspace of the system eigenstates without requiring any prior detailed knowledge about the system Hamiltonian. The procedure is simulated for optimally controlled population transfer experiments in the system of two degrees of freedom. To show the feasibility of steering the dynamics to lie in a specified subspace, the learning algorithms guiding the dynamics are presented along with frequency filtering. The results demonstrate that the optimal control fields derive the system to the desired target state through the desired subspace.

• 설비공학논문집
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• 제16권11호
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• pp.1068-1076
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• 2004

Technology on the proportional integral (PI) control have grown rapidly owing to the needs for the robust capacity of the controllers from industrial building sectors. However, PI controller requires tuning of gains for optimal control when the outside weather condition changes. The present study presents the possibility of reinforcement learning (RL) control algorithm with PI controller adapted in the HVAC system. The optimal design criteria of RL controller was proposed in the Environment Chamber experiment and a theoretical analysis was also conducted using TRNSYS program.