• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.847-852
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• 1993

In this paper, we present a recursive algorithm for the auto-tuning of PID controllers by optimizing a GPC criterion. Also, we develop an intelligent PID controller by combination of a recursive algorithm together with a supervisor, that allows to adjust the main controller parameters (prediction horizon, control weighting, sample time etc.) using some simple rules which is mainly built up through relay tuning experiments. The intelligent PID controller has been implemented successfully on an IBM PC/AT and some simulation results are presented.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.809-811
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• 1999

The three-mode PID controller is widely used in plant because control algorithm is simple and tuning method is general. But the conventional PID controller can not have the both purpose of setpoint tracking and disturbance rejection at the same time. In this paper, we studied the application 2DOF PID controller to pneumatic control valve through simulation and experiments. Results are Presented a satisfactory response

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.981-986
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• 1992

In order to implement the digital PID control algorithm, it is necessary to consider the effect of the finite word length(FWL). In this paper, we show the FWL effect in the digital PID controllers. The conception analyse the effects of the signal quantization error in the digital PID algorithm and the coefficient wordlength determined from performance criteria with the statistical wordlength concept. Throughout this paper, it is dealt with the type of controller structure based delta operator the delta operator has such advantages are superior rounfoff noise perfoff noise performance, more accurate coefficient repersentation, and less sensitive control law.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.127-127
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• 2000

The anti-windup schemes developed so far are summarized and the similarities/differences schemes are discussed. The anti-windup schemes are applied to a DC servomotor control system with PID controller to perform comparative study and sensitivity analysis. Based on those results, some criteria for choosing anti-windup scheme are suggested. The results of this study provide a very useful guideline for selecting and designing the anti-windup scheme for various types of PID control systems.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1120-1122
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• 2005

인터넷의 급속한 보급으로 인해 데이터 전송 시 발생하는 공간상의 제약을 쉽게 극복 할 수 있게 되어 전 세계 어디서든지 데이터를 주고받을 수 있게 되었다. 이러한 인터넷 웹기반의 장점을 살려서 그동안 실험 연구용으로 사용하던 서보시스템의 PID 제어방법을 인터넷을 기반으로 한 원격제어 시스템으로 구현하였다. 본 논문에서는 DC 서보 모터와 모터 제어 보드, NI사의 DAQ, PC로 시스템을 구현 하였다. UI(User Interface)는 LabVIEW 프로그램을 이용하여 GUI(Graphical User Interface)로 DC 서보 모터의 제어와 작동상태의 모니터링이 용이하도록 하였고, 최적의 PID 이득값을 설정하여 원하는 속도 응답 특성이 양호한 제어를 할 수 있게 하였다. 더 나아가 PID 제어 방법을 원격 실시간의 가상 실습이 가능한 e-Learning에 적용 할 수 있음을 확인하였다.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.69-77
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• 1999

This paper describes the design of fuzzy digital PID controller using simplified indirect inference method. First, the fuzzy digital PID controller is derived from the conventional continuous time linear digital PID controller. Then the fuzzification, control-rule base, and defuzzification using SIM in the design of the fuzzy digital controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional digital PID controller, which has the same linear structure, but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIM is applied, the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated the superior to the control performance of the one proposed by D. Misir et al.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.178-180
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• 1986

본 연구에서는 산업용 팩키지 보일러의 최적한 연소제어를 위하여 O/sub 2/ 제어기의 구성 및 PID제어 알고리즘을 도입하고 그것에 따른 하드웨어 및 소프트웨어를 고찰하였으며 그 결과 하드와이어드 논리제어기나 기존의 PC보다 분산제어의 효율적 처리가 가능하였다. BD/Micro PC 시스템에서 시퀀스 제어를 필요로하는 기능은 BD PC가, 아날로그 시스템을 다루는 PID 제어같은 기능은 .mu.C가 담당함으로서 제어범위가 넓어져 각종의 연산기능확대, BD PC와 .mu.C와의 데이터 링크, 그리고 고장진단등의 기능이 추가되었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.348-354
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• 1999

In recent years, a PID controller has been used as a major control method in real control processes. This controller requires a determination of PID control gains. But it is difficult to select the best gains theoretically. Thus there have been many approaches to determine them empirically Most of them are based on experience and knowledge. In this paper, we proposed a tuning method of the PID Parameters by using neural network. To show effectiveness of the proposed method, the simulation of DC motor and one link manipulator position control is carried out.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.171-174
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• 2007

A realization for FF-PID(Feed-Forward PID) controlling system with backward propagation algorithm and image pattern recognition is presented in this paper. The pattern recognition used backward propagation of nervous network is teaming. FF-PID is enhanced the response characteristic of moving image by using the controlling value which is output error for the target value of nervous system. In conclusion of experiment, the system is shown that the response is worked as 2.7sec that is enhanced round 15% in comparison with general difference image algorithm. The system is able to control a moving object with effect.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.49-54
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• 2003

In this paper, we propose a controller with the self-organizing neural network compensator for compensating PID controller's response. PID controller has simple design method but needs a lot of trials and errors to determine coefficients. A neural network control method does not have optimal structure as the parameters are pre-specified by designers. In this paper, to solve this problem, we use a self-organizing neural network which has Back Propagation Network algorithm using a Gaussian Potential Function as an activation function of hidden layer nodes for compensating PID controller's output. Self-Organizing Neural Network's learning is proceeded by Gaussian Function's Mean, Variance and number which are automatically adjusted. As the results of simulation through the second order plant, we confirmed that the proposed controller get a good response compare with a PID controller. And we implemented the of controller performance hydraulic servo motor system using the DSP processor. Then we observed an experimental results.