• Journal of Power Electronics
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• v.15 no.2
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• pp.338-345
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• 2015

The time-optimal control for boost converters can achieve the minimum recovery time. However, their output voltage deviation is quite large. Since the minimum output voltage deviation and minimum recovery time cannot be obtained at the same time, a novel energy control is proposed to achieve a superior tradeoff between them in this paper. The peak value of the inductor current can be decreased as well. Its control parameter is easy to choose. When compared with the conventional control methods, the proposed control shows a better dynamic performance. Experimental results, which are in agreement with the theoretical analysis, are provided to verify the proposed control method.

• Journal of Power Electronics
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• v.16 no.2
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• pp.584-597
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• 2016

This paper focuses on an improvement in the transient performance of Boost converters when the load changes abruptly. This is achieved on the basis of the nature trajectory in Boost converters. Three key aspects of the transient performance are analyzed including the storage energy change law in the inductors and capacitors of converters during the transient process, the ideal minimum voltage deviation in the transient process, and the minimum voltage deviation control trajectory. The changing relationship curve between the voltage deviation and the recovery time is depicted through analysis and simulations when the load suddenly increases. In addition, the relationship curve between the current fluctuation and the recovery time is obtained when the load suddenly decreases. Considering the aspects of an increasing and decreasing load, this paper proposes the transient performance synthetic optimized trajectory and control laws. Through simulation and experimental results, the transient performances are compared with the other typical three control methods, and the ability of proposed synthetic trajectory and control law to achieve optimal transient performance is verified.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.6
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• pp.634-640
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• 2009

The plate manufacturing processes are composed of the reheating furnace, finishing mill, cooling process and hot leveling. The finishing rolling mill (FM) as a reversing mill has produced the plate steel through multiple pass rolling. The automatic gauge control (AGC) is employed to maintain the thickness tolerance. The high grade products are forming greater parts of the manufacturing and customers are requiring strict thickness margin. For this reason, the advanced AGC method is required instead of the conventional AGC based on the PI control. To overcome the slow response performance of the conventional AGC and the thickness measurement delay, a fuzzy AGC based on the thickness deviation and its trend is proposed in this paper. An embedded controller with the fuzzy AGC has been developed and implemented at the plate mill in POSCO. The fuzzy AGC has dynamically controlled the roll gap in real time with the programmable logic controller (PLC). On line tests have been performed for the general and TMCP products. As the results, the thickness deviation range (maximum - minimum of the inner plate) is averagely from 0.3 to 0.1 mm over the full length. The fuzzy AGC has improved thickness deviation and completely satisfied customer needs.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.9
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• pp.380-387
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• 1986

We have developed a dual control algorithm by means of innovations approach and established the stability of dual by introducing the pole-placement method suggested by Berger on the non-dual control. The dual controller realizing this algorithm decreases control loss sharply when compared with that of a non-dual controller, and shows the characteristics of suppressing the output deviation in transient state effectively. The total control energy and the accumulated square misdistance of this dual controller are shown to be 1-10% and 0.1-10% of those of CE control, respectively. Consequently this controller solves the non-minimum phase problem encountered when discretizing the system equation, and can be used to overcome the uncertainty of system effectively by adjusting the learning rate of the controller.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.30.6-30
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• 2001

We build near minimum-time trajectory planning algorithm for Wheeled mobile robots (WMRs) With Piece-Wise Constant control voltages satisfying i) initial and final postures and velocities as well as ii) voltage constraints We consider trajectory planning problem for cornering motion with a path-deviation requirement for obstacle avoidance. We divide our trajectory planning algorithm for cornering motion into five ordered sections: translational, transient, rotational, transient, and translational sections. Transforming dynamics into uncorrelated form with respect to translational and rotational velocities, we can make controls for translation/rotational velocities to be independent. By planning each section with constant voltages, and integrating five sections with adjustment of numbers of steps, the overall trajectory is planned. The performance is very close to the minimum-time solution, which is validated via simulation studies.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.676-680
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• 1994

Three synchronic variables (Deviation Time, Fairness Time, Synchronic Time) are defined for Timed Place Petri Nets (TPPN). These parameters show the dependency between the firing of transition subsets in the time domain by different values. The approaches in this paper can be used to find synchronic relations in Stochastic Petri Nets. This paper presents how to decide the minimum resources required to a Flexible Manufacturing Cell using Synchronic Time concept.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.16-16
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• 2000

This paper describes a new structure re create a pseudo Gaussian function network (PGFN). The activation function of hidden layer does not necessarily have to be symmetric with respect to center. To give the flexibility of the network, the deviation of pseudo Gaussian function is changed according to a direction of given input. This property helps that given function can be described effectively with a minimum number of center by PGFN, The distribution of deviation is represented by level set method and also the loaming of deviation is adjusted based on it. To demonstrate the performance of the proposed network, general problem of function estimation is treated here. The representation problem of continuous functions defined over two-dimensional input space is solved.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.375-378
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• 1991

This paper presents a design method of synchronous generator excitation controller using self-tuning PID algorithm. Controller parameter is determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameter of controller. minimum variance algorithm using the recursive leastsquare(RLS) indentification method is adopted and the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping and conversion characteristics. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performances than conventional controller.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.4
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• pp.29-36
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• 2009

The fuzzy controller of the FFH(Fuel Fired Heater) used for vehicle is designed in this study. Two of the most important things of the pre-heater are how fast it can be at the set temperature and how to reduce the temperature deviation in the space to a minimum. The temperature deviation of the existed FFH with PI controller for temperature controller was reduced. Also, the fuzzy controller improved the response characteristics, and then the performance was inspected. When setting the temperature in this designed fuzzy controller, it took 12 minutes in the existed PI control method to reach $25^{\circ}C$. However, it took 9 minutes and 20 seconds in the fuzzy control method. Therefore, it is proved that the fuzzy controller is better than the existed one with fast response performance as 2 minutes 40 seconds. The temperature deviation was $2.4^{\circ}C$ in the existed control method but $1.6^{\circ}C$ in the designed fuzzy controller. Accordingly, the temperature deviation was improved too.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.247-264
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• 2008

This paper considers the integrated process control procedure for detecting special causes in an ARIMA(0,1,1) process that is being adjusted automatically after each observation using a minimum mean squared error adjustment policy. It is assumed that a special cause can change the process mean and the process variance. We derive expressions for the process deviation from target for a variety of different process parameter changes, and introduce a control chart, based on the generalized likelihood ratio, for detecting special causes. We also propose the integrated process control scheme bases on the future loss. The future loss denotes the cost that will be incurred in a process remaining interval from a true out-of-control signal.