• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.117-120
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• 2003

A method for PID controller tuning based on process models for unstable processes was introduced. The optimal. proportional and derivative gains of the AMBs were determined by the tuning method and utilized for the chatter stability analysis in order to search for the chatter-free cutting region. The stability analysis results showed that the optimal gains give wider chatter-free cutting region, and as a result the proposed tuning method was confirmed to be an effective tuning method for determining the optimal gains of the AMBs.

• 한국정밀공학회지
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• 제16권6호
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• pp.25-35
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• 1999

This paper presents a control gain tuning scheme for multi-axis PID control systems by Taguchi method. As an experimental set-up, a parallel mechanism machine tool has been selected. This machine has eight servodrives and each servodrive has four control gains, respectively. Therefore, total 32 control gains have to be tuned. Through a series of design of experiments, an optimal and robust set of PID control gains is tuned. The index of the sum of position error and velocity error is reduced to 61.4% after the experimental gain tuning regardless of the feedrate variation.

• 한국정밀공학회지
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• 제13권5호
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• pp.74-83
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• 1996

An iterative tuning technique is derived for PID controllers which are widely used in industries. The tuning algorithm is based upon a fuzzy indirect reasoning method and an iterative technique. The PID gains for the first tuning action are determined by a method which is modified from the Ziegler-Nichols step response method. The first PID gains are determined to obtain a control performance so close to a design performance that the following tuning process can be made effectively. The design paramaters are given as time-domain variables which human is familiar with. The results of simulation studies show that the proposed tuning method can produce an effective tuning for arbitrary design performances.

• 한국위성정보통신학회논문지
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• 제11권4호
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• pp.39-43
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• 2016

본 논문은 조향구조를 갖는 이동로봇의 조향 제어를 위해 PID 제어기의 이득을 튜닝 방법을 제안한다. PID 이득을 설정하는 다양한 방법들이 제시되고 연구되고 있다. 이득은 지글러-니콜스의 계단형 입력으로부터 이득을 얻는 방법으로 얻어진 이득을 이동로봇에 적용하고 이를 시험하여 다시 2차 전달함수에 의해 새로운 이득을 계산하였다. 얻어진 새로운 이득으로 응답시간 및 유지오차율에 관한 실험을 수행하여 PID 자동 튜닝의 성능을 확인하였다. 유지시간, 응답시간 및 수렴시간에 대한 실험결과로 이동로봇의 조향 시스템에서 사용이 가능하고 응답 시간이 빠르게 도달할 수 있으며 안정하게 제어됨을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.109-109
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• 2000

In process industries, more than 90% of the control loops have PID controller. Futhermore, the most control systems are using classical PID controllers for their process control. Various auto-tuning methods of PID gains using relay-feedback are presented recently. In order to get the desired control performance, the correct tuning of PID controller is very important. This paper suggests how to tune of digital PID gains using information for both the Nyquist critical point by conventional method and another point by the relay feedback and hidden time-delay term. Simulation results show that the proposed controller has better performance than the conventional method.

• 전기학회논문지
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• 제57권3호
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• pp.518-526
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• 2008

The fuzzy self-tuning PID controller is a PID controller with a fuzzy logic mechanism for tuning its gains on-line. In this structure, the proportional, integral and derivative gains are tuned on-line with respect to the change of the output of system under control. This paper deals with two types of fuzzy self-tuning PID controllers, rule-based fuzzy PID controller and learning fuzzy PID controller. As a medical application of fuzzy PID controller, the proposed controllers were implemented and evaluated in a laparoscopic surgery robot system. The proposed fuzzy PID structures maintain similar performance as conventional PID controller, and enhance the position tracking performance over wide range of varying input. For precise approximation, the fuzzy PID controller was realized using the linear reasoning method, a type of product-sum-gravity method. The proposed controllers were compared with conventional PID controller without fuzzy gain tuning and was proved to have better performance in the experiment.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 추계학술대회 논문집
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• pp.182-186
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• 1992

A self tuning technique is derived for PID controllers which are widely used in industries. The tuning algorithm is based upon a fuzzy indirect reasoning method and an iterative technique. The fuzzy technique is considered to obtain ease and simplicity of tuning process. The PID gains for the first tuning action are determined by a method which is modified from the Ziegler-Nichols step response method. The first PID gains are determined to obtain a control performance so close to a design performance that the followed tuning process can be made effectively. The design parameters are given as time-domain variables which human is familiar with. The results of simulation studies show that the proped tuning method can produce an effective tuning for arbitaray design performances.

• Journal of Advanced Marine Engineering and Technology
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• 제33권7호
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• pp.1003-1011
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• 2009

This study aims at precise control of oil outlet temperature in the oil cooler system of machine tools for enhancement of working speed and processing accuracy. PID control logic is adopted to obtain desired oil outlet temperature of the oil cooler system with hot-gas bypass method. We showed that the gains of PID controller could be easily determined by using gain tuning methods to get the gain of PID controller without any mathematical model. We also investigated various gain tuning methods to design the gains of PID and compared each control performance for selecting the optimal tuning method on the hot gas bypass method through experiments. Moreover, we confirmed excellent control performance with proposed PI controller gain even though disturbances were abruptly added to the experimental system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.476-479
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• 1992

This paper presents a neural network method for tuning PlD controller of a time-varying process. Three gains of PlD controller are tuned for a certain desirable response pattern by back-propagation neural network. The neural network is trained using changes of output features vs. changes of PlD gains. But sometimes it needs longer training time and larger structure to train the correlation between the process and controller on entire region of the process. The difficulty in system identification is that the inverse function of the system can not be clearly stated. To cope with the problem, we do not train the neural network to respond correctly for the entire regions but train for only local region where the system is heading toward by training the neural network and tuning of the PlD controller. It may be trained for fine-tuning itself. Simulation results show that the adaptive PID controller using neural network trained in the local area performs remarkably for time-varying second order process.

• 한국정밀공학회지
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• 제13권5호
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• pp.139-147
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• 1996

PID control has been widely used for real control systems. Particularly, there are many researches on control schemes of tuning PID gains. However, to the best of our knowledge, there is no result for discrete-time systems with unknown time-delay and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown papameters and unknown time-delay system. A numerical simulation was presented to illustrate the effectiveness of this method.