• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1092-1095
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• 1996

In this paper The tuning of PID controller for multi input-output is studied by using fuzzy inference. State of coupling is estimated by fuzzy inference, its results is used for tuning of PID controller to get optimum P,I,D parameter with regard to state of coupling. This method is simulated to Turbo-generating system with $2{\times}2$ multi input-output and made with electronic circuit, its response is very satisfactory.

• 전자공학회논문지SC
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• 제44권6호
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• pp.21-28
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• 2007

Mutiresolution proportional-integral-derivative(MRPID) 제어기는 웨이브렛 기반의 다해상도 응답을 이용해서 에러 신호에 포함되어 있는 잡음과 외란을 제거하는 필터 역할을 해준다. 다해상도 응답의 특징상 샘플링 주파수가 높을 경우 상대적으로 고주파성분이 남아있음으로 인해 응답속도가 떨어지는 대신에 오버슈트가 제거되고, 낮을 경우 신호 성분이 제거되므로 인해 응답속도가 향상되지만 오버슈트가 증가 되는 결과를 보였다. 본 논문에서는 proportional-integral-derivative(PID) 제어기와 MRPID 제어기의 응답을 이용한 샘플링 주파수를 설정하는 기법과, MRPID 제어기의 특성을 고려한 파라미터 설정기법을 제안한다. 모의실험을 통해서 제안된 기법의 타당성을 검증하였다.

• 한국조명전기설비학회지:조명전기설비
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• 제9권3호
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• pp.97-103
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• 1995

In this paper, for fuzzy control of linear servo system using the moving coil type linear DC motor, we propose a new fuzzy control method using parameter tuning for membership functions. A proposed fuzzy control method tunes parameters of membership function to have an appropriate control input signal for system when error exceeds predefined value and makes an inference using conventional fuzzy control rules when error reduces to a predefined value. To verify usefulness of a proposed fuzzy control method, making simulation and experiment, we compare with characteristics for conventional fuzzy control method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.316-318
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• 1993

In order to estimation the optimum PID parameter of the turbine speed controller, the response cure of the object plant was compared with the reference pattern and then the magnitude peak value error and peak time error was calculated. With the calculated errors as input into the Fuzzy inference Method was introduced to propose the tuning method for each parameter. And the computer simulation was performed with the above Fuzzy inference method in which the Chunju hydro power plant turbine governor system was used as a model. This Study also aims to develop the exclusive tuner for govenor using industrial computer.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.214-217
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• 1993

This paper presents a new identification method which utilizes fuzzy inference in parameter identification. The proposed system has an additional control loop where a real plant is replaced by a plant model. The control system to be designed is to satisfy the following specifications: 1) It has zero steady-state error. 2) It has adequate damping characteristics. 3) 1),2) satisfied, it has a shortest rise-time. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. This method is effective in auto-tuning because the response of the closed loop is verified. The proposed method is tested in simulation for several plants with first- order lags and dead-times. The results show that the proposed method is effective in practical use.

• 한국조명전기설비학회지:조명전기설비
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• 제9권1호
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• pp.63-66
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• 1995

PDI 제어기는 많은 서보 제어 시스템에 사용되고 있다. 하지만 제어 시스템이 가변부하일 경우에 정밀한 제어는 어렵게 된다. 이에 대한 보완적인 한 방법으로, 본 논문에서는 가변부하일 경우 퍼지 규칙에 의해 PID 제어기의 매개변수를 자동 동조하는 방법을 제시하였다. PID 제어기의 매개변수는 부하 변화에 따라 퍼지 규칙에 의해 결정된다. 퍼지 자동 동조에 의한 정밀한 제어 기능은 모의실험에 의해 확인하였다.

• 전자공학회논문지S
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• 제36S권11호
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• pp.22-33
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• 1999

본 논문에서는 시스템의 차수가 고차이고 잡음과 시간지연이 있으며 파라미터가 변하는 비최소위상 시스템에 적응할 수 있는 다변수 일반화 자기동조 제어기의 설계 하중다항식 계수들을 온-라인으로 조정하는 방법을 제안한다. 다변수 일반화 최소분산 자기동조 제어기의 파라미터는 순환최소자승법으로 추정하고 설계 하중다항식 계수들의 값은 확률근사법인 Robbins-Monro알고리듬을 이용하여 자동 조절하였다. 제안한 다변수 자기동조 방법은 극제한방법보다 간단하고 효과적이다. 컴퓨터 시뮬레이션을 통해 제안한 방법이 시스템의 파라미터가 변하고 시스템의 영점이 단위원 밖에 있는 고차 다변수 시스템에 잘 적응함을 보였다.

• 대한전기학회논문지:전력기술부문A
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• 제49권12호
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• pp.589-594
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• 2000

The fuzzy controllers have been applied to the power system stabilizer due to its excellent properties on the nonlinear systems. But the design process of fuzzy controller requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This process is time consuming task. This paper presents an parameters tuning method of the fuzzy power system stabilizer using the genetic algorithm and simulated annealing(SA). The proposed method searches the local minimum point using the simulated annealing algorithm. The proposed method is applied to the one-machine infinite-bus of a power system. Through the comparative simulation with conventional stabilizer and fuzzy stabilizer tuned by genetic algorithm under various operating conditions and system parameters, the robustness of fuzzy stabilizer tuned by proposed method with respect to the nonlinear power system is verified.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.206-211
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• 1993

This paper presents a new identification method which utilizes fuzzy inference in parameter identification. The proposed system has an additional control loop where a real plant is replaced by a plant model. The control system to be designed is to satisfy the following specifications: 1) It has zero steady-state error. 2) It has adequate damping characteristics. 3) 1),2) satisfied, it has a shortest rise-time. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. This method is effective in auto-tuning because the response of the closed loop is verified. The proposed method is tested in simulation for several plants with high-order lags and dead-times.

• Communications for Statistical Applications and Methods
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• 제24권6호
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• pp.673-683
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• 2017

The least absolute shrinkage and selection operator (LASSO) has been a popular regression estimator with simultaneous variable selection. However, LASSO does not have the oracle property and its robust version is needed in the case of heavy-tailed errors or serious outliers. We propose a robust penalized regression estimator which provide a simultaneous variable selection and estimator. It is based on the rank regression and the non-convex penalty function, the smoothly clipped absolute deviation (SCAD) function which has the oracle property. The proposed method combines the robustness of the rank regression and the oracle property of the SCAD penalty. We develop an efficient algorithm to compute the proposed estimator that includes a SCAD estimate based on the local linear approximation and the tuning parameter of the penalty function. Our estimate can be obtained by the least absolute deviation method. We used an optimal tuning parameter based on the Bayesian information criterion and the cross validation method. Numerical simulation shows that the proposed estimator is robust and effective to analyze contaminated data.