• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1242-1244
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• 1999

AVR parameter tuning for voltage control of power system generators has generally been done with the open-circuit model of the synchronous generator. When the generator is connected on-line and operating at rated load conditions, the AVR operates in an entirely different environment from the open-circuit conditions. This paper describes a new method for AVR parameter tuning using optimization technique with on-line linearized system model. As this method considers not only the on-line models but also the off-line open-circuit models, AVR parameters tuned by this method can give the sufficiently stable performance at the open-circuit commissioning phase and give the desired performance at the operating conditions. Also this method estimates the optimum parameters for desired performance indices that are chosen for satisfying requirements in some practical applications, the performance of the AVR can satisfy the various requirements.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.505-505
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• 2000

Controlling the process by PID controller is widely used in industry by applying Ziegler-Nichols method in analyzing parameter of the controller. However, in fact. it is still necessary to tune parameter in order to obtain the best process response. This paper presents a Self-Tuning PID controller utilizes the personal computer to synthesize and analyze controller parameter as well as tune for appropriate parameter by using Dahlin method and Extrapolation. Experimental results using a Self-Tuning PID controller to control water level and temperature, it is found that the controller being developed is able to control the process very effectively and provides a good response similar to the controller used in the industry.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.704-707
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• 1997

In this paper, we present a fuzzy logic based tuner for continuous on-line tuning of PID controllers. The essential idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a singler parameter .alpha., then to use an on line fuzzy logic to self-tune the parameter. The adaptive scaling makes the controller robust against large variations in parametric and dynamics uncertainties in the plant model. New self-tuning controller has the ability to decide when to use PI or PID control by extracting process dynamics from relay experiments. These scheme lead to improved performance of the transient and steady state behavior of the closed loop system, including processes with nonminimum phase processes.

• 전기학회논문지
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• 제58권4호
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• pp.655-664
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• 2009

This paper, Part 1, describes the effective dual-input PSS parameter design procedure for the IEEE Type PSS2A against the Dangjin 612 MVA thermal plant's EX2000 excitation system. The suggested tuning technique used the model-based PSS tuning method and consisted of three steps: 1) generation system modeling; 2) determination of PSS2A model parameters using linear, time-domain transient and 3-phase simultaneous analyses, and 3) field testing and verification, which are described in Part 2. The effective PSS2A model parameters of EX2000 system in the Dangjin T/P #4 were designed according to the suggested procedure, and verified by using three analyses.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.95-103
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• 2001

The purpose of Introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. The efficiency of a combined power plant with the gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a combined 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul, Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controllers.

• 전자공학회논문지SC
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• 제40권4호
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• pp.264-274
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• 2003

본 논문에서는 잡음과 시간지연이 존재하며 시스템 파라미터가 변하는 비선형 비최소위상 시스템에 적응하는 신경회로망이 결합된 PID구조를 갖는 일반화 최소분산 자기동조제어기를 제안한다. PID구조를 갖는 자기동조는 PID제어기처럼 구조가 간단하고 계통을 정밀하게 제어하는 자기동조 제어기의 특성을 그대로 유지할 수 있다. 일반화 최소분산 자기동조 제어기 파라미터는 비선형 시스템을 선형시스템으로 간주하고 순환최소자승법으로 추정하며 설계계수의 값은 확률근사법인 Robbins-Monro 알고리듬을 이용하여 자동조정하였다. 역전파 학습 알고리듬을 사용하는 신경회로망 제어기는 비선형 부분의 제어를 보상하기 위해 필터된 기준입력과 필터된 플랜트 출력이 같도록 제어값을 출력한다. 컴퓨터 시뮬레이션을 통해 제안한 방법이 시스템의 파라미터가 변하는 비최소위상 시스템에 잘 적응함을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집(한일합동학술편); 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.817-826
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• 1987

An offset-free self-tuning control with pole placement (STCPP) and a recursive parameter estimation with multiple and variable forgetting factors (REWF), together with their application to a real plant, are described. There are two different types of offset-free STCPP; their features are analysed and discussed. REMVF employs as many forgetting factors as parameter estimates. It is suitable when parameters to be estimated are changing at different rates. The offset-free STCPP and REMVF have been successfully applied to a real plant, giving excellent results.

• 제어로봇시스템학회논문지
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• 제2권1호
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• pp.14-20
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• 1996

This paper presents a self tuning method of a velocity type PID controller for minimum or non-minimum phase systems with time delays. The velocity type PID control structure is determined in the process of minimizing the variance of the auxilliary output, and self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design parameter. This method is simple and effective compared with other existing methods[1,2]. Numerical examples are included to illustrate the procedure and to show the performance of the control system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.295-298
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• 1996

In this paper, a self-tuning optimal control algorithm is proposed to retain the optimal performance of an active suspension system, when the vehicle has some time varying parameters and parameter uncertainties. We consider a 2 DOF time-varying quarter car model which has the parameter variation of sprung mass, suspension spring constant and suspension damping constant. Instead of solving algebraic riccati equation on line, we propose a neural network approach as an alternative. The optimal feedback gains obtained from the off line computation, according to parameter variations, are used as the neural network training data. When the active suspension system is on, the parameters are identified by the recursive least square method and the trained neural network controller designer finds the proper optimal feedback gains. The simulation results are represented and discussed.

• 한국컴퓨터정보학회논문지
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• 제22권12호
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• pp.27-34
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• 2017

Design of an intelligent controller for efficient control in smart building is one of the effective technologies to reduce energy consumption by reducing response time with keeping comfortable level for inhabitants. In this paper, we focus on how to find major parameters in order to enhance the ability of HVAC(heating, ventilation, air conditioning) PID controller. For the purpose of that, we use machine learning technologies for tuning HVAC devices. We show the simulation results to illustrate the behavioral relation of whole system and each control parameter while learning process.