• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.205-208
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• 2000

In this paper, we'll show that an improved PDFF controller is obtained by substituting a feedforward compensator in the existing PDFF system with a dual-input describing function, and the controller has the ability of adjusting the bandwidth of a system as well as the phase margin simultaneously. The effectiveness of the proposed controller is confirmed by applying to the DC-motor position control system. As the results of simulation, we know that it is possible to design a controller by which the bandwidth of the closed system and its phase margin are easily adjusted.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.788-791
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• 2006

Fuzzy theory has been used effectively to control the nonlinear system since Mamdani successively adopted fuzzy theory in the steam-engine control problem in 1973. Truckbacker-upper control problem originally proposed by Nguyen and Widrow become a standard highly nonlinear control problem. In this paper, we designed adaptive fuzzy membership functions for speed control as well as steering control. In other words, an adaptive fuzzy control system for truck backer-upper problem useful for practical adaptation is proposed. Experimental results by simulations prove the effectiveness of the proposed system.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.702-708
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• 1987

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.102-107
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• 2008

We propose an autotuning algorithm for PI controller with unknown plant. The proposed algorithm uses a saturation function and time delay element as a test signal. Since the integral element of PI controller reduces a phase margin in the closed loop system, the closed loop system could be resulted in unstable with PI controller. To avoid unstable in the closed loop system with PI controller, the proposed algorithm identifies one point information in the 3rd quadrant of Nyquist plot with a time delay element. The proposed method improves an accuracy of one point identified information with one saturation function. We demonstrate a performance of the proposed method via a simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11C
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• pp.1073-1078
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• 2007

In this paper, we propose an iterative mixed norm image restoration algorithm using multi regularization parameters. A functional which combines the regularized $l_2$ norm functional and the regularized $l_4$ norm functional is proposed to efficiently remove arbitrary noise. The smoothness of each functional is determined by the regularization parameters. Also, a regularization parameter is used to determine the relative importance between the regularized $l_2$ norm functional and the regularized $l_4$ norm functional using kurtosis. An iterative algorithm is utilized for obtaining a solution and its convergence is analyzed. Experimental results demonstrate the capability of the proposed algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.2
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• pp.92-100
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• 1992

플렉시블한 관절을 가지고 있는 로보트에 대하여 계단(step) 혹은 경사(ramp) 함수로 기준입력이 주어졌을 때, 모델의 불확실성이나 외란 아래에서 추적오차가 없는 디지찰 제어기법을 제시하고 실제로 실험을 통하여 제어기를 MC 68000으로 구현함으로써 제안한 제어 알고리즘의 유용성을 보였다. 제어기 설계에 있 어서 고려한 사항들은 비선형 마찰력, 중력에 의한 외란, 구동기와 부하사이의 뒤틀림 스프링 효과, 구리고 측 정할 수 없는 상태변수들이다. 또한 미분불가능한 쿨롱마찰로 인하여 전체 시스템이 이산/연속 혼성 시스템이 되어 출력에서 나타나는 리미트 싸이클을 해석/추정하기 위하여 혼성 시스템에서의 기술함수(Describing Function) 법을 제시하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.105-110
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• 1998

본 논문에서는 퍼지 로직을 이용하여 ATM 망의 ABR(Available Bit Rate) 트래픽 제어를 위한 효과적이고, 안정적인 피드백 제어 알고리즘을 제안한다. 기존 알고리즘들의 단점을 보완하면서, 망 내의 상황이 변하더라도 자가 학습 기능(self-learning capability)을 이용하여 파라미터 값들을 상황에 맞게 변화시키는 퍼지 로직을 이용한 새로운 제어알고리즘을 제안한다. 제안된 알고리즘은 Projection algorithm을 이용하여, 과거의 데이터로부터 다음 순간의 ABR 버퍼의 크기를 예측하며 퍼지 제어기의 출력 함수 파라미터들은 성능함수를 최소화하도록 학습된다. 제안된 알고리즘은 안정성(stability)이 보장되며, Upstream bottleneck 환경등의 특수하고, 제한된 상태에서도, 요구되는 QoS와 max-min fairness가 만족되고, 링트 효율을 극대화 할 수 있음을 시뮬레이션을 통하여 입증한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.390-396
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• 1998

본 논문은 퍼지 논리 제어기(FLC)의 근사화 능력과 제어 성능을 동시에 향상시키는 정확한 무게 중심(Center Of Gravity; COG) 비퍼지화기를 제안한다. 본 논문은 비퍼지화 과정이 최적 선택의 한 과정이며 비퍼지화 방법의 적절한 선택이다. 제안한 COG 비퍼지화기의 정확성은 출력 소속 함수를 여러 개의 설계 파라메터(중신, 폭, 변경자(modifier))로 나타내고 이들 설계 파라메터들을 학습과 진화의 Lamarckian 상호 적응에 의하여 갱신함으로써 얻어진다. 이러한 학습과 진화의 상호 적응은 학습하지 않는 경우 보다 빠르게 최적 COG 비퍼지화기를 얻도록 하며, 보다 넓은 범위의 탐색으로최적해를 찾을 가능성을 높여 준다. 제안한 설계 방법은 목적 함수의 가중치를 조절하여 높은 근사화 능력, 높은 제어 성능, 또는 이들간의 균형된 성능을 갖는 다양한 특정 응용형(Application-specific)COG 비퍼지화기를 제공한다. 제안한 상호적응 COG 비퍼지화기의 설계방법을 트럭 후진 주차 제어 문제에 적용하여, 각각 시스템 오차와 평균 추적 거리로 나타내어진 근사화 능력과 제어 성능을 기존의 COG 비퍼지화기와 비교한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1370-1377
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• 2004

Optimal control gain for time-delay systems is made by an optimal control gain for delay-free systems multiplied by a state transition function for the delay time. The optimal control gain for delay-free systems is obtained by pushing two zeros of the PID controller closely to a larger pole of the second order plant. Thus the optimal tuning of PID controller for time-delay second order system is able to be obtained by calculation for the state transition function.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.239-245
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• 2012

This paper proposes a novel optimum design method for the PID controller of magnetic levitation-based Rail-Guided Vehicle(RGV) by a genetic algorithm using clone selection method and a new performance index function with performances of both time and frequency domain. Generally, since an attraction type levitation system is intrinsically unstable and requires a delicate controller that is designed considering overshoot and settling time, it is difficult to completely satisfy the desired performance through the methods designed by conventional performance indexes. In the paper, the conventional performance indexes are analyzed and then a new performance index for Maglev-based RGV is proposed. Also, an advanced genetic algorithm which is designed using clonal selection algorithm for performance improvement is proposed. To verify the proposed algorithm and the performance index, we compare the proposed method with a simple genetic algorithm and particle swarm optimization. The simulation results show that the proposed method is more effective than conventional optimization methods.