• Journal of the Korean Statistical Society
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• 제17권1호
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• pp.1-8
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• 1988

Kernel estimates of an unknown regression function are studied. Bandwidth selection rule minimizing integrated absolute error loss function is considered. Under some reasonable assumptions, it is shown that the optimal bandwidth is unique and can be computed by using bisection algorithm. Adaptive bandwidth selection rule is proposed.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.145-150
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• 1997

In this paper is studied a method of fuzzy logic control based on possibly inconsistent if-then rules representing uncertain knowledge or imprecise data. In most cases of practical applications adopting fuzzy if-then rule bases, inconsistent rules have been considered as ill-defined rules and, thus, not allowed to be in the same rule base. Note, however, that, in representing uncertain knowledge by using fuzzy if-then rules, the knowledge sometimes can not be represented in literally consistent if-then rules. In this regard, when it is hard to obtain consistent rule base, we propose the weighted rule base fuzzy logic control depending on output performance using neural network and we will derive the weight update algorithm. Computer simulations show the proposed method has good performance to deal with the inconsistent rule base fuzzy logic control. And we discuss the real application problems.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.144-147
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• 2001

This paper presents adaptive fuzzy controller which is uncertainty or unknown variation in different parameters with nonlinear system of helicopter. The proposed adaptive fuzzy controller applied TSK(Takagi-Sugeno-Kang) fuzzy system which is not only low number of fuzzy rule, and a linear input-output equation with a constant term, but also can represent a large class of nonlinear system with good accuracy. The adaptive law was designed by using Lyapunov stability theory. The adaptive fuzzy controller is a model reference adaptive controller which can adjust the parameter $\theta$ so that the plant output tracks the reference model output. First of all, system of helicopter was considered as stopping state, and design of controller was simulated from dynamics equation with stopping state. Results show that it is controlled more successfully with a model reference adaptive controller than with a non-adaptive fuzzy controller when there is a modelling error between system and model or a continuous added noise in such unstable system.

• Structural Engineering and Mechanics
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• 제43권3호
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• pp.349-370
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• 2012

Variable-node finite element families, termed (4 + k + l + m + n)-node elements with an arbitrary number of nodes (k, l, m, and n) on each of their edges, are developed based on the generic point interpolation with special bases having slope discontinuities in two-dimensional domains. They retain the linear interpolation between any two neighboring nodes, and passes the standard patch test when subdomain-wise $2{\times}2$ Gauss integration is employed. Their shape functions are automatically generated on the master domain of elements although a certain number of nodes are inserted on their edges. The elements can provide a flexibility to resolve nonmatching mesh problems like mesh connection and adaptive mesh refinement. In the case of adaptive mesh refinement problem, so-called "1-irregular node rule" working as a constraint in performing mesh adaptation is relaxed by adopting the variable-node elements. Through several examples, we show the performance of the variable-node finite elements in terms of accuracy and efficiency.

• 컴퓨터교육학회논문지
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• 제6권4호
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• pp.95-113
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• 2003

본 논문에서는 기존의 LCMS에서 사용되는 평가시스템에 퍼지 추론 규칙을 이용한 적응형 퍼지평가시스템(AFES ; Adaptie Fuzzy Evaluation System)을 제안한다. AFES 는 학습자가 하나의 학습코스(learning course)에 들어가기 전에 퍼지진단평가(fuzzy diagnostic evealuation)를 통해 학습자에게 코스수준(course level)을 부여한다. 학습자는 코스수준에 따른 맞춤식 학습경로(learning path)로 학습을 종료한 후, 퍼지최종평가(fuzzy final evaluation)를 통해 최종성적(final grade)을 AFES 으로부터 부여 받는다. AFES의 가장 큰 특징은 최종성적의 점수 부여 규칙에 있는데, 만약 서로 다른 학습자가 동일한 문제 수에 대하여 같은 수의 정답을 냈더라도, AFES 는 125 가지 퍼지 추론 규칙(fuzzy reasoning rule)에 의거하여 탄력적으로 서로 다른 최종성적을 학습자에게 부여한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.161.4-161
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• 2001

This paper presents adaptive control of robot manipulator using neuro-fuzzy controller Fuzzy logic is control incorrect system without correct mathematical modeling. And, neural network has learning ability, error interpolation ability of information distributed data processing, robustness for distortion and adaptive ability. To reduce the number of fuzzy rules of the FLS(fuzzy logic system), we consider the properties of robot dynamic. In fuzzy logic, speciality and optimization of rule-base creation using learning ability of neural network. This paper presents control of robot manipulator using neuro-fuzzy controller. In proposed controller, fuzzy input is trajectory following error and trajectory following error differential ...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.584-588
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• 1991

This paper presents a fuzzy adaptive controller which can improve the control policy automatically. Adaptation is achieved by the addition of on-line identification of the fuzzy inverse model using input-output data pairs of the process. Starting with an initial crude control rule, the adaptive controller matches the model to the process to self-tune the controller. The control algorithm needs much less memory of computer than other SOC algorithms.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2441-2443
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• 2003

This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. No a priori information on bounding constants of uncertainties including reconstruction errors and optimal fuzzy parameters is needed. The control law and the update laws for fuzzy rule structure and estimates of fuzzy parameters and bounding constants are determined so that the Lyapunov stability of the whole closed loop system is guaranteed. The computer simulation results for an inverted pendulum system show the performance of the proposed robust adaptive fuzzy controller.

• 한국전산구조공학회논문집
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• 제32권3호
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• pp.173-181
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• 2019

제한된 실험 데이터로부터 확률분포함수를 추정하기 위해서 KDE가 많이 사용되고 있다. KDE에 의한 분포함수는 대역폭 선택법에 따라서 실험 데이터에 대해 평활하거나 과대적합된 커널 추정치를 생성한다. 본 연구에서는 Silverman's rule of thumb, rule using adaptive estimate, oversmoothing rule을 사용해서 각 방법에 따른 정확성과 보수적인 성향을 비교하였다. 비교를 위해서 단봉분포와 다봉분포를 가지는 실제 모델을 가정하고 통계적 시뮬레이션을 수행한 다음 다양한 데이터의 개수에 따른 추정된 분포함수의 정확도와 보수성을 비교하였다. 또한, 간단한 신뢰성 예제를 통해 대역폭 선택법에 따른 KDE의 추정된 분포가 신뢰성 해석 결과에 어떻게 영향을 미치는지 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.162.1-162
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• 2001

In this paper, the adaptive fuzzy system is used as an adaptive approximator for robot nonlinear dynamic. A theoretical justification for the adaptive approximator is proving that if the representive point(RP or switching function) and its derivative in sliding mode control are used as the inputs of the adaptive fuzzy system, the adaptive fuzzy system can approximate robot nonlinear dynamics in the neighborhood of the switching surface. Thus the fuzzy controller design is greatly simplified and at the same time, the fuzzy control rule can be obtained easily by the reaching condition. Based on this, a new method for designing an adaptive fuzzy control system based on sliding mode is proposed for the trajectory tracking control of a robot with unknown nonlinear dynamics.