• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.17-19
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• 1997

원자력 발전소용 증기발생기의 수위제어에 기존의 경우 주로 PI제어기를 이용하는데 반해 본 논문에서는 기타의 주급수유량에 대한 주증기 유량의 변화를 2-자유도 PID제어기를 이용해 제어하는 문제를 연구하였다. 2-자유도 PID제어기의 파라메터 .alpha..betha..gamma.를 외란에 대해 가인하도록 하고 설정치변화에 대해서는 기존의 PID 파라메터가 부담하도록 함으로서 외란 및 설정치 모두에 대해 고찰한 결과 기존의 PI제어기에 비해 성능이 우수함을 나타내었다.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.608-613
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• 1999

This thesis aims at developing of a digita governor system for the steam turbine generator on the Buk-Cheju Thermal Power Plant of KEPCO. The steam turbine generator of the Buk-Cheju Thermal Power Plant is modelled. As a hardware platform, a triple modular system which is fitted 32-bit microprocessor of Motorola company to perform the digital governor system is used. The parameters of the PID controller algorithm in the speed control block is tuned on the basis of the estimated model.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.826-831
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• 2007

In this paper, we proposed new method of soft-motor control which is control method allowing motor control within control stage by using EtherCAT which is real time motion control network of high speed. We also evaluated performance of the system and verified possibility and effectiveness of application into real system through experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.346-349
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• 2003

For a traveling crane, various control methods such as neural network predictive control and TDOFPID(Two Degree of Freedom Proportional Integral Derivative) are studied. So in this paper, we proposed improved navigation method to reduce transfer time and sway with anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the NNPPID(Neural Network Predictive PID) controller to control the precise move and speedy navigation. The proposed predictive control system is composed of the neural network predictor, TDOFPID controller, and neural network self-tuner. We analyzed ASC(Automated Stacking Crane) system and showed some computer simulations to prove excellence of the proposed controller than other conventional controllers.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.350-353
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• 2003

In this paper, we proposed the method to design fuzzy controller using the experience of the operating expert and experimental numeric data for the robust control about the noise and disturbance instead of the traditional PID controller for the main steam temperature control of the thermal power plant. The temperature of main steam temperature process has to be controlled uniformly for the stable electric power output. The process has the problem of the hunting for the cases of various disturbances. In that case, the manual action of the operator happened to be introduced in some cases. We adopted the TSK (Takagi-Sugeno-Kang) model as the fuzzy controller and designed the fuzzy rules using the informations extracted directly from the real plant and various operating condition to solve the above problems and to apply practically. We implemented the real fuzzy controller as the Function Block module in the DCS(Distributed Control System) and evaluated the feasibility through the experiment81 results of the simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.146-152
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• 2002

Mold level control has been a major control task for continuous casting plants. The system involves nonlinearities such as stick-slip friction in the sliding gate, time-delay, friction force variations between molten steel and the inner wall of mold, and nozzle logging/unclogging. These complex problems should be solved to control mold level for steel cast. In this paper, we propose a neural fuzzy mold level control technique for solving these complex problems and give experiment studies to show the mold level control in continuous casting process.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.691-695
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• 1998

Most of systems has nonlinearity . And also accurate modelings of these uncertain nonlinear systems are very difficult. In this paper, a fuzzy modeling technique for the stabilization control of an IP(inverted pendulum) system with nonlinearity was proposed. The fuzzy modeling was acquired on the basis of ANFIS(Adaptive Neuro Fuzzy Infernce System) which could learn using a series of input-output data pairs. Simulation results showed its superiority to the PID controller. We believe that its applicability can be extended to the other nonlinear systems.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.29-34
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• 2010

This paper presents an intelligent learning controller for repetitive walking motion of biped walking robot. The proposed learning controller consists of an iterative learning controller and a direct learning controller. In the iterative learning controller, the PID feedback controller takes part in stabilizing the learning control system while the feedforward learning controller plays a role in compensating for the nonlinearity of uncertain biped walking robot. In the direct learning controller, the desired learning input for new joint trajectories with different time scales from the learned ones is generated directly based on the previous learned input profiles obtained from the iterative learning process. The effectiveness and tracking performance of the proposed learning controller to biped robotic motion is shown by mathematical analysis and computer simulation with 12 DOF biped walking robot.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.598-601
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• 2001

As many sensors and actuators are used in many automated system, various industrial networks are adopted for digital control system. In order to take advantages of the networking, however, the network implementation should be carefully designed to satisfy real-time requirements considering network delays. This paper presents the implementation scheme of a networked control system via Profibus-DP network. More specifically, the effect of the network delay on the control performance was evaluated on a Profibus-DP testbed, and a GA based PID tuning algorithm is proposed to demonstrate the fesibility of the networked control system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.177-181
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• 2003

PID(Proportional-Integral-Derivative)제어기는 제어악고리즘의 단순성과 실 현장에서의 강인성 등으로 산업용 보일러의 제어시스템서 주로 이용되어 왔다. 그러나 다중 루프를 가진 보일러 시스템에서는 루프간의 상호 간섭 영향 등으로 부하 변화에 따라 요구되는 증기(steam)압력, 증기 유량(steam flow)변화 등을 동시에 만족하도록 급수 유량, 연교 유량, 공기 유량 등을 PlH제어기만으로 제어하는 것은 어렵다. 본 연구에서는 보일러 시스템의 다목적 성능 최적화에 각각의 적합도 함수 $f_{a}$ , $f_{b}$, $f_{c}$를 정의하고 면역 알고리즘을 이용해 최적화를 구하고 그 결과에 대한 특성과 유효성을 검토하였다.다.다.