• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.84-89
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• 2003

Fuzzy controller is one of the succeed controller used in the process control in case of model uncertainties. But it my be difficult to fuzzy controller to articulate the accumulated knowledge to encompass all circumstance. Hence, it is essential to provide a tuning capability. There are many parameters in fuzzy controller can be adapted, scale factor tuning of normalized fuzzy controller is one of the adaptation parameter. Two adaptation methods are implemented in this work on an experimental thermal process, which simulate heating process in liquefied petroleum gases (LPG) recovery process in one of petrochemical industries: Gradient decent (GD) adaptation method; supervisory fuzzy controller. A comparison between the two methods is discussed.

• 산업기술연구
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• 제13권
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• pp.33-41
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• 1993

In this paper, a new LMS algorithm with a fuzzy variable step size (FVS LMS) is presented. The change of step size ${\mu}$, at each iteration which is increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. As a measure of the misadaptation degree, the norm of the cross correlation between the estimation error and input signal is used. Simulation results are presented to compare the performance of the FVSS LMS algorithm with the normalized LMS algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.224-227
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• 1993

In this paper, a new LMS algorithm with a variable step size (VVS LMS) is presented. The change of step size .mu. at each iteration, which increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. The norm of the cross correlation between the estimation error and input signal is used. As a measure of the misadaptation degree. Simulation results are presented to compare the performance of the VSS LMS algorithm with the normalized LMS algorithm.

• Earthquakes and Structures
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• 제11권2호
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• pp.347-369
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• 2016

The main objective of this paper is the robust multi-objective optimization design of semi-active tuned mass damper (STMD) system using genetic algorithms and fuzzy logic. For optimal design of this system, it is required that the uncertainties which may exist in the system be taken into account. This consideration is performed through the robust design optimization (RDO) procedure. To evaluate the optimal values of the design parameters, three non-commensurable objective functions namely: normalized values of the maximum displacement, velocity, and acceleration of each story level are considered to minimize simultaneously. For this purpose, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solutions. The torsional effects due to irregularities of the building and/or unsymmetrical placements of the dampers are taken into account through the 3-D modeling of the building. Finally, the comparison of the results shows that the probabilistic robust STMD system is capable of providing a reduction of about 52%, 42.5%, and 37.24% on the maximum displacement, velocity, and acceleration of the building top story, respectively.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2003년도 하계학술대회 논문집
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• pp.149-152
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• 2003

플랜트 모델이나 경험에 근거하여 설계된 퍼지제어기를 실제 플랜트에 적용할 경우, 모델링 오차와 플랜트에 대한 관련지식의 부족으로 만족할 만한 제어 결과를 나타내지 못할 경우가 있다. 이 경우 제어성능을 향상시키기 위해 제어기의 제어인자를 다시 조정하여야 하고, 이 조정과정은 시행착오 방법으로 수행되기 때문에 많은 시간과 비용을 필요로 한다. 본 논문에서는 정규화 된 오차와 오차 변화량를 사용하여 플랜트 응답에 따라 입력과 출력의 적절한 스케일 계수를 조정하는 퍼지제어기를 제안한다. 정규화 된 오차를 출력 소속함수의 중심과 폭에 곱해 출력 범위를 재조정하고, 플랜트 응답에 의해 입력의 스케일 계수를 결정한다. 이를 확인하기 위해 2차 플랜트에 적용하여 모의 실험을 수행하였다.