• 조명전기설비학회논문지
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• 제27권4호
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• pp.48-53
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• 2013

In general, the LLC resonant topology consists of three stages as; square wave generator, resonant network, and rectifier network. LLC resonant converter has the time slowly varying parameters. However, the power LEDs as the load of LLC converter can be regarded as fast time varying parameters. In this paper, the mathematical model of half-bridge resonant converter including with the power LEDs is introduced for the current controller design model. Using this controller design model, the parameter adaptive output feedback controller will be designed to control the power LEDs current. In order to show the validities of the proposed model, the parameter adaptive output feedback controller, the experimental investigation will be presented.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.859-871
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• 2003

In this paper we introduce some adaptive M-estimators using selector statistics to estimate the slope of regression model under the symmetric and continuous underlying error distributions. This selector statistics is based on the residuals after the preliminary fit L$_1$ (least absolute estimator) and the idea of Hogg(1983) and Hogg et. al. (1988) who used averages of some order statistics to discriminate underlying symmetric distributions in the location model. If we use L$_1$ as a preliminary fit to get residuals, we find the asymptotic distribution of sample quantiles of residual are slightly different from that of sample quantiles in the location model. If we use the functions of sample quantiles of residuals as selector statistics, we find the suitable quantile points of residual based on maximizing the asymptotic distance index to discriminate distributions under consideration. In Monte Carlo study, this adaptive M-estimation method using selector statistics works pretty good in wide range of underlying error distributions.

• 한국지능시스템학회논문지
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• 제13권1호
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• pp.85-90
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• 2003

본 논문에서는 퍼지모델을 이용하여 비선형 시스템을 위한 적응 PID 제어기 설계 방법을 제안한다. TSK 퍼지모델을 이용하여 제어 입력의 오차를 예측하고 그 오차로부터 PID제어기의 파라미터를 적응시킨다. TSK 퍼지모델 또한 플랜트의 실제 출력과 모델 출력을 비교하여 모델 파라미터의 적응이 가능하도록 하였다. 제안된 방법으로 비선형의 플랜트에 대한 모호성, 파라미터의 변화 등에 적응할 수 있는 PID 제어기의 설계가 가능하였다. 그리고 몇 개의 비선형 시스템에 대한 시뮬레이션으로 제안된 알고리즘의 유용성도 확인되었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.1041-1044
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• 1988

This paper considers the design problem of adaptive filters based an the state-space models for linear discrete-time stationary stochastic signal processes. The adaptive state estimator consists of both the predictor and the sequential prediction error estimator. The discrete Chandrasakhar filter developed by author is employed as the predictor and the nonlinear least-squares estimator is used as the sequential prediction error estimator. Two models are presented for calculating the parameter sensitivity functions in the adaptive filter. One is the exact model called the linear innovations model and the other is the simplified model obtained by neglecting the sensitivities of the Chandrasekhar X and Y functions with respect to the unknown parameters in the exact model.

• Transactions on Control, Automation and Systems Engineering
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• 제4권4호
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• pp.330-340
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• 2002

In this Paper. a non-linear approach to a design of model reference adaptive control is presented. The approach is demonstrated by a case study of a simple single-pole and no zero, linear, discrete-time plant. The essence of the idea is to generate a full non-linear model of the plant dynamics and the parameter adaptation dynamics as a gradient descent algorithm with respect to a Riemannian metric. It is shown how a Riemannian metric can be chosen so that the modelled plant dynamics do in fact match the true plant dynamics. The performance of the proposed scheme is compared to a traditional model reference adaptive control scheme using the classical sensitivity derivatives (Euclidean gradients) for the descent algorithm.

• 대한기계학회논문집A
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• 제29권1호
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• pp.88-95
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• 2005

This paper presents a design scheme of model reference adaptive control incorporating a Neural Network for a pneumatic servo system. The parameters of discrete-time model of plant are estimated by using the recursive least square method. Neural Network is utilized in order to compensate the nonlinear nature of plant such as compressibility of air and frictions present in cylinder. The experiment of a trajectory tracking control using the proposed control scheme has been performed and its effectiveness has been proved by comparing with the results of a model reference adaptive control.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.40.5-40
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• 2001

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-S) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control.

• 한국산업정보학회논문지
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• 제22권2호
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• pp.79-89
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• 2017

본 연구에서는 적응형혼합유전알고리즘(Adaptive Hybrid Genetic Algorithm: AHGA) 접근법을 이용한 폐쇄루프 공급망(Closed-Loop Supply Chain: CLSC) 모델 최적화를 다루고 있다. CLSC 모델 구축을 위해 공급업체(Part Supplier), 제품제조업체(Product Manufacturer)등으로 구성된 전방향물류(Forward Logistics)와 수집업체(Collection Center), 회복센터(Recovery Center)등으로 구성된 역물류(Reverse Logistics)를 함께 고려하고 있다. 제안된 CLSC 모델은 수리모형(Mathematical Model)으로 표현되며, AHGA접근법을 이용해 이행되어 그 최적해를 구하게 된다. 수치실험에서는 기존연구에서 제안된 몇몇 접근법과 AHGA 접근법을 함께 사용하여 그 수행도를 비교분석하였다.

• 한국지능시스템학회논문지
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• 제6권2호
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• pp.97-105
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• 1996

본 논문에서는 퍼지모델을 이용한 비선형 공정의 적응모델예측제어가 제안된다. 모델예측제어의 저긍구조는 순환 퍼지모델링을 통해 구현된다. 사용된 퍼지모델의 후건부가 입, 출력 변수의 선형식이기 때문에, 전체 공정의 모델을 구하고 이를 이용하여 미래 공정출력을 구한 후 비용함수를 최로로하는 제어법칙은 일반형 예측제어(GPC)와 같은 형태가 된다. 제안된 적응 퍼지모델 예측제어는 퍼지모델이 가지는 본래적인 비선형성으로 인해 비선형공정을 우수한 성능으로 제어한다. 공정제어입력의 변화량을 출력값으로 하는 적응 퍼지모델 예측제어(AFMPC)인 경우, 상수의 기준입력에 대해 정상상태가 없고 매우 우수한 성능을 보인다. 제안된 제어구조의 특성 및 성은 비선형 공정의 모의 실험에 의해 검증한다.

• Earthquakes and Structures
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• 제11권6호
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• pp.1077-1099
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• 2016

One of the main shortcomings in the current passive base isolation system is lack of adaptability. The recent research and development of a novel adaptive seismic isolator based on magnetorheological elastomer (MRE) material has created an opportunity to add adaptability to base isolation systems for civil structures. The new MRE based base isolator is able to significantly alter its shear modulus or lateral stiffness with the applied magnetic field or electric current, which makes it a competitive candidate to develop an adaptive base isolation system. This paper aims at exploring suitable control algorithms for such adaptive base isolation system by developing a close-loop semi-active control system for a building structure equipped with MRE base isolators. The MRE base isolator is simulated by a numerical model derived from experimental characterization based on the Bouc-Wen Model, which is able to describe the force-displacement response of the device accurately. The parameters of Bouc-Wen Model such as the stiffness and the damping coefficients are described as functions of the applied current. The state-space model is built by analyzing the dynamic property of the structure embedded with MRE base isolators. A Lyapunov-based controller is designed to adaptively vary the current applied to MRE base isolator to suppress the quake-induced vibrations. The proposed control method is applied to a widely used benchmark base-isolated structure by numerical simulation. The performance of the adaptive base isolation system was evaluated through comparison with optimal passive base isolation system and a passive base isolation system with optimized base shear. It is concluded that the adaptive base isolation system with proposed Lyapunov-based semi-active control surpasses the performance of other two passive systems in protecting the civil structures under seismic events.