• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.375-378
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• 1991

This paper presents a design method of synchronous generator excitation controller using self-tuning PID algorithm. Controller parameter is determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameter of controller. minimum variance algorithm using the recursive leastsquare(RLS) indentification method is adopted and the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping and conversion characteristics. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performances than conventional controller.

• 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.

• 제어로봇시스템학회논문지
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• 제5권6호
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• pp.744-752
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• 1999

In this paper, we studied the response characteristics of $\alpha$, $\beta$ separated type, combined type, PI typed, and feedforward type in 2DOF-PID controller through the simulation and the experiments designed with the multivariable flow control system. The parameters $\alpha$ and $\beta$ give an affect to characteristics of controller in separated type but $\gamma$ does not give an affect to the characteristics of 2-DOF PID. The more $\beta$ increases, the more overshoot decreases and especially, in case of PI type represent clearly. The $\alpha$, $\beta$ separated type has a very small overshoot and its magnitudes in 2-DOF PID onctroller increases in order of $\alpha$, $\beta$ combined type, PI type, feedforward type, conventional type. The response characteristics of simulation are similar to that of experiments but the experimental characteristics in the multivariable flow control system has the delayed response. The time delay of response in experiments depends on 2-DOF parameter $\alpha$, $\beta$, $\gamma$ and the overshoot increase as the $\alpha$, $\beta$, $\gamma$ increase. So, we can have a satisfactory response by tuning D gain.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1327-1334
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• 1999

The stabilization control of ball-beam system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of classical methods such as the PID and the full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Therefore, in this paper, three improved design techniques of stabilization controller for a ball-beam system were proposed. These parameter tuning methods in the double PID controller(DPIDC), the FSFC and the a sliding mode controller(SMC) were dependent upon the Real Value Elitist Genetic Algorithm (RVEGA). Finally, by applying the DPIDC, the FSFC and the Real Variable Elitist Genetic Algorithm based Sliding Mode Control(RVEGA SMC) to the stabilizations of a ball-beam system, the performances of the RVEGA SMC technique were showed to be superior to those of two other type controllers.

• 동력기계공학회지
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• 제9권4호
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• pp.194-201
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• 2005

In this paper, we propose an adaptive mechanism based on humoral immune algorithm and neural network identifier technique. It is also applied for an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To slove this problem, we use the neural network identifier technique for modeling the plant humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. Finally, the experimental results for control of steering and speed of AGV system illustrate the validity of the proposed control scheme. Also, these results for the proposed method show that it has better performance than other conventional controller design method such as PID controller.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.228-231
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• 2000

A hybrid fuzzy controller by means of the genetic algorithms is presented. The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PlD's output in steady state by a fuzzy variable. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller. A auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller using genetic algorithms. The algorithms estimates automatical Iy the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA three kinds of estimation modes are effectively utilized. The HFCs are applied to the second process with time-delay. Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed in ITAE(Integral of the Time multiplied by the Absolute value of Error ) and other ways.

• 한국정보통신학회논문지
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• 제2권1호
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• pp.19-26
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• 1998

본 논문에서는 추적 성능 개선을 위해 기존의 신경망 제어기에 PID제어기를 직렬로 연결하여 시뮬레이션 결과를 고찰했다. 추적 성능을 평가하기 위해 신경망모델은 2계층으로 구성하고 Widrow-Hoff델타 규칙을 이용하여 예측 오차가 최소화되도록 정규적인 동특성을 학습하였다. 이 학습 결과, 기존의 신경망제어기의 경우보다 PID를 연결하였을 경우가 추적 성능이 다소 개선되었음을 확인했으며, 251샘플에서 추적할 플랜트 파라메터가 시변인 경우에도 빠른 속도로 수렴되는 결과를 얻었다.

• 전자공학회논문지SC
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• 제44권1호
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• pp.25-32
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• 2007

본 논문은 시간 응답을 과도응답과 정상상태 응답으로 분류하여 1차의 지연시간을 포함한 공정을 동정하는 새로운 모델링 방법을 제시했다. 먼저 공정의 입.출력 데이터를 분석하여 공정의 상태를 정상상태 응답과 과도상태 응답으로 분류한다. 그 다음 최소 자승법을 사용하여 정상상태 응답은 하나의 1차의 지연시간을 갖는 공정으로 추정하고, 과도상태 응답은 여러 개의 모델로 나누어 모델링 한다. 최적의 PID 동조법으로는 지연시간을 보상하는 Smith- Predictor 구조에 성능지수 ITAE값이 최소가 되도록 설계하였다. 시뮬레이션을 통하여 다양한 공정에 대하여 본 논문에서 제안한 방법을 적용하여, 모델축소 방법의 정확성 및 제어기 성능의 개선을 보였다.

• 한국생산제조학회지
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• 제23권3호
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• pp.318-324
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• 2014

Recent years have witnessed a growing demand for a wide variety of high-performance industrial robots. In this paper, for accurate gain tuning of a 6-axis articulated industrial robot with reduced noise, a program routine for a dynamic signal analyzer (DSA) using the frequency response method will be programmed using $LabVIEW^{(R)}$. Then, robot transfer functions can be obtained experimentally using the frequency response method with the DSA program. Data from the robot transfer functions are transformed into Bode plots, based on which an optimal gain tuning will be executed. Gain tuning can enhance the response quality of the output signal for a given input signal during real-time control of the robot. The effectiveness of our proposed technique will be verified by implementation with a (lab-manufactured) 6-axis articulated industrial robot (hereinafter called "RS2") and comparison with the zero position gain tuning, as well as other positions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.