• Journal of Advanced Marine Engineering and Technology
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• v.38 no.8
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• pp.1000-1003
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• 2014

There are 70 vertical and 70 horizontal correctors for Pohang Light Source. Until mid of 2000, power supplies for these correctors were based on 1990's technology, so the global orbit feedback system was not possible with poor 12 bit resolution. A new task force team was assembled to develop new power supplies with BESSY type DAC cards. After the project, two vertical correctors in each lattice were connected with new power supplies, and the global orbit feedback was available within the accuracy of 5 microns. However, this replacement was not enough to satisfy the beam stability requirement of 2 microns for PLS. We have launched another power supply design based on all digital technology. This attempt was completed within a year, and 80 units were assembled in house. Currently, the global orbit feedback system is running successfully with new digital power supplies and the compensation of chamber motion due to the thermal load by using digital displacement transducers attached on each BPMs.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.453-455
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• 1997

일반적으로 제철공정에서 각 공정사이의 철판의 속도와 장력은 브라이드롤을 이용하여 제어하는데 여기서 입력 측의 브라이드롤은 장력을 제어하고 출력 측의 브라이드롤은 공정의 속도를 제어한다. 이와 같은 방법은 시스템 기동의 순간을 포함하여 공정속도의 변경이 있을 경우 제철 공정 상에서는 특히 철판의 높은 탄성에 기인하여 시스템이 상당히 불안정하게 된다. 본 논문에서는 각 전동기가 정해진 역할에 따라 독립적으로 장력 혹은 공정속도를 제어하고 장력의 모델링에서 비선형의 요소를 되먹임하여 원래의 시스템을 선형화시켰고 이때 미분관측기를 이용하였다. 이 제어기의 장점은 무엇보다도 독립적인 역할의 분담으로 인해 다수의 전동기로 확장이 용이하도록 하는 것이다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.185-188
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• 1997

In this paper, we execute identification, linearization, and control of a nonlinear system using recurrent neural networks. In general nonlinear control system become complex because of nonlinearity and uncertainty. And though we compose nonlinear control system based on the model, it is difficult to get good control ability. So we identify the nonlinear control system using the recurrent neural networks and execute feedback linearization of identified model, In this process we choose the optional linear system, and the system which will have to be feedback linearized if trained to follow the linearity between input and output of the system we choose. We the feedback linearized system by applying standard linear control strategy and simulation. And we evaluate the effectiveness by comparing the result which is linearized theoretically.

• Proceedings of the KWS Conference
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• 2005.06a
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• pp.63-65
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• 2005

Because of simple principal and low cost, resistance spot welding has been used a lot for joining the sheet metal in automotive manufacturing process. Welding current, welding time, and force are the most important variables in resistance spot wording. Air guns have hem still used widely. The requirement of synchronizing between robot and weld-gun has become bigger as the field has been automated. The number of servo-gun in the field is trending upward because there're advantages as like to synchronize with robot and to control the stroke path and force by programming on servo-gun system. But no cleared force control method is suggested on servo-gun system until now. In this study, we proved the feedback current of the servo-motor can be used to an excellent force measuring sensor and the force is controlled by the feedback current. And we also detected force lowering during welding cycle on the servo-gun system and solved by compensated force control.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.10A
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• pp.1639-1644
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• 2001

Two decision feedback equalizer structures employing recurrent neural network (RNN) used for non-linear channels with severe intersymbol interference (ISI) and non-linear distortion are proposed in this paper, which skillfully put the traditional decision feedback structure for linear channels equalization into RNN, replace decision feedback signal with training signal in the learning process and adaptively adjust the learning step. Simulative results of the first type of two new equalizer structures have shown that it has better equalization performances than traditional recurrent neural network equalizer (RNNE) under the same condition.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2636-2638
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• 2000

In this paper, we show the simple methods of designing the Smith predictor for the long dead time processes. We are using the relay feedback to model the processes in the second-order plus dead time structure. The model is able to represent a various class of processes dynamics including low- or high-order, and monotonic or oscillatory process. A PID type controller is proposed for the main controller in the Smith controller, which insure the stability of overall system. Simulation Examples are also provided to illustrate the effectiveness and applicability of the proposed controller.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4270-4284
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• 2019

This study presents a reference model (RM) and the architecture of a cognitive health advisor (CHA) that integrates information with ambient intelligence. By controlling the information using the CHA platform, the reference model can provide various ambient intelligent solutions to a user. Herein, a novel approach to a CHA RM based on evolutional cyber-physical systems is proposed. The objective of the CHA RM is to improve personal health by managing data integration from many devices as well as conduct a new feedback cycle, which includes training and consulting to improve quality of life. The RM can provide an overview of the basis for implementing concrete software architectures. The proposed RM provides a standardized clarification for developers and service designers in the design and implementation process. The CHA RM provides a new approach to developing a digital healthcare model that includes integrated systems, subsystems, and components. New features for chatbots and feedback functions set the position of the conversational interface system to improve human health by integrating information, analytics, and decisions and feedback as an advisor on the CHA platform.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.395-400
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• 2015

Obtaining the parameters for PID controllers based on limit cycle information for the process in a relay controlled feedback loop has become an accepted practical procedure. If the form of the plant transfer function is known, exact expressions for the limit cycle frequency and amplitude can be derived so that their measurements, assumed error free, can be used to calculate the true parameter value. In the literature, parameter estimation for an assumed form of the plant transfer function has generally been considered for disturbance free cases, except a recently published work of the author. In this paper additional simulation results are reported on exact parameter estimation from relay autotuning under static load disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.299-302
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• 1996

A control algorithm is proposed for nonlinear multi-input multi-output(MIMO) batch processes by combining quadratic iterative learning control(Q-ILC) with model predictive control(MPC). Both controls are designed based on output feedback and Kalman filter is incorporated for state estimation. Novelty of the proposed algorithm lies in the facts that, unlike feedback-only control, unknown sustained disturbances which are repeated over batches can be completely rejected and asymptotically perfect tracking is possible for zero random disturbance case even with uncertain process model.

• 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..