• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.206-209
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• 1999

Conventional target tracking techniques are primarily based on Kalman filtering or probabilistic data association(PDA). But it is difficult to perform well under a high cluttered tracking environment because of the difficulty of measurement, the problem of mathematical simplification and the difficulty of combined target detection for tracking association problem. This paper deals with an analysis of target tracking problem using fuzzy-logic theory, and determines fuzzy rules used by a fuzzy tracker, and designs the fuzzy tracker by using fuzzy rules and Kalman filtering.

• 인터넷정보학회논문지
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• 제2권2호
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• pp.117-126
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• 2001

본 논문에서는 지식기반 시스템의 퍼지 생성규칙을 술어논리 수준에서 표현할 수 있는 퍼지 Pr/T 네트를 제안한다. 퍼지 Pr/T 네트는 Pr/T 네트의 퍼지 확장이다. 퍼지 Pr/T 네트를 기반으로 퍼지추론 알고리즘을 제안한다. 퍼지추론 알고리즘은 퍼지 생성규칙에서 퍼지개념에 따라 적절한 믿음 값 함수를 사용하므로 다른 방법보다 더 사람의 직관과 추론에 가깝다.

• 한국지능시스템학회논문지
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• 제4권1호
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• pp.24-34
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• 1994

A RMFSOC(Reference Model Following Self-Organizing Fuzzy Logic Controller) is propose in this paper. In the RMFSOC, the refernce model is introduced, where the desired control performance can be specified by an operator of the controlled process. The self-organizing level of the RMFSOC organizes the control rules of FLC which make the process output follow the reference model output. In addition, for the use of preventing improper modifications of control rules, a complementary decission rule is induced from the possible relations between the process output and reference model output. Through a simulation study, it is shown that the robustness of the control system using the proposed RMFSOC to the set-point changes and distur bances can be greatly improved being conpared with that of the control system using the Procyk and Mamdani's SOC.

• 한국지능시스템학회논문지
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• 제5권1호
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• pp.25-32
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• 1995

In this paper, the FLVSC (Fuzzy Logic Variable Structure controller), of which control rules are extracted from the concepts of the VSC(Variable Structure control) is proposed and diesgned for drum motor(BLDC motor) in home VCR. The FLC (Fuzzy Logic Controller) based on linguistic rules has the advantages of not needing of some exact mathermatical model for plant to be controlled. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of distrubances, parameter variations and uncertainites in a sliding mode. In addition, the method has the properties of the FLC-noise rejection capability etc. The computer simulation and experiment using DSP(TMS320C30) have been carried out for the servo control of VCR drum motor to show the usefulness of the proposed method.

• 제어로봇시스템학회논문지
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• 제10권12호
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• pp.1223-1232
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• 2004

We present a new technique to the design and real-time implementation of fuzzy control system basedon digital signal processors in order to improve the precision and robustness for system of industrial robot in this paper. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C80 is used in implementing real time fuzzy control to provide an enhanced motion control for robot manipulators. In this paper, a Self-Organizing Fuzzy Controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a Fuzzy Logic Controller, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult Self-Organizing Fuzzy Controller is proposed for a hierarchical control structure consisting of basic and high levels that modify control rules. The proposed Self-Organizing Fuzzy Controller scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for a Dual-Arm robot with eight joints.

• Journal of Electrical Engineering and Technology
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• 제11권2호
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• pp.309-319
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• 2016

This paper presents a new recognition and classification method for power quality (PQ) disturbances on the basis of pattern linguistic values. This method solves the difficulty of recognizing disturbances rapidly and accurately by using fuzzy logic. This method uses classification disturbance patterns to define the linguistic values of fuzzy input variables and used the input variables of corresponding disturbance pattern to set membership functions. This method also sets the fuzzy rules by analyzing the distribution regularities of the input variable values. One characteristic of this method is that the linguistic values of fuzzy input variables and the setting of membership functions are not only related to the input variables but also to the character of classification disturbance and the classification results. Furthermore, the number of fuzzy rules is equal to the number of disturbance patterns. By using this method for disturbance classification, the membership function and design of fuzzy rules are directly related to the objective of classification, thus effectively reducing the complexity of the design process and yielding accurate classification results. The classification results of the simulation and measured data verify the feasibility and effectiveness of this method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.993-996
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• 1993

This paper addresses the structure and its associated learning algorithms of a feedforward multi-layered connectionist network, which has distributed learning abilities, for realizing the basic elements and functions of a traditional fuzzy logic controller. The proposed neural-network-based fuzzy logic control system (NN-FLCS) can be contrasted with the traditional fuzzy logic control system in their network structure and learning ability. An on-line supervised structure/parameter learning algorithm dynamic learning algorithm can find proper fuzzy logic rules, membership functions, and the size of output fuzzy partitions simultaneously. Next, a Reinforcement Neural-Network-Based Fuzzy Logic Control System (RNN-FLCS) is proposed which consists of two closely integrated Neural-Network-Based Fuzzy Logic Controllers (NN-FLCS) for solving various reinforcement learning problems in fuzzy logic systems. One NN-FLC functions as a fuzzy predictor and the other as a fuzzy controller. As ociated with the proposed RNN-FLCS is the reinforcement structure/parameter learning algorithm which dynamically determines the proper network size, connections, and parameters of the RNN-FLCS through an external reinforcement signal. Furthermore, learning can proceed even in the period without any external reinforcement feedback.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권2호
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• pp.159-165
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• 2002

This paper proposes a GA and Gradient Descent Method-based method for choosing an appropriate set of fuzzy rules for classification problems. The aim of the proposed method is to fond a minimum set of fuzzy rules that can correctly classify all training patterns. The number of inference rules and the shapes of the membership functions in the antecedent part of the fuzzy rules are determined by the genetic algorithms. The real numbers in the consequent parts of the fuzzy rules are obtained through the use of the descent method. A fitness function is used to maximize the number of correctly classified patterns, and to minimize the number of fuzzy rules. A solution obtained by the genetic algorithm is a set of fuzzy rules, and its fitness is determined by the two objectives, in a combinatorial optimization problem. In order to demonstrate the effectiveness of the proposed method, computer simulation results are shown.

• 한국화재소방학회논문지
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• 제18권4호
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• pp.42-51
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• 2004

본 논문은 열과 연기농도를 입력변수로 갖는 퍼지로직을 적용한 화재감지시스템을 제시한 연구이다. 본 논문에서 제시한 화재감지시스템은 열과 연기농도를 입력신호로 받아들이고 이를 통하여 화재가능성이 추론되는 퍼지추론시스템을 포함하고 있다. 이 추론시스템의 조건부(antecedent part)는 fuzzy 단일 값(singleton)으로 열과 연기농도가 입력되도록 하였고, 결론부(conclusion part)는 화재가능성으로 적용하였다. 또한 퍼지추론을 위하여 적용된 membership함수는 삼각형 membership함수이다 추론하는 방법은 Mamdani가 제안한 minimum 연산을 사용하였다. 그리고 이러한 계산을 위하여 Matlab 프로그램을 사용하였고 이 프로그램을 이용하여 GUI(graphic user interface)기반의 화재감지프로그램을 개발하였다. 이와 같은 퍼지로직이 적용된 화재감지시스템의 신뢰성을 검증하기 위하여 불꽃화재와 훈소화재에 대한 실험을 통하여 추론되는 화재가능성을 분석하였다. 그 결과 본 연구의 퍼지로직을 적용한 화재감지시스템은 연소상황에 따라 비교적 정확하게 화재가능성을 추론하였다.

• 논리연구
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• 제21권1호
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• pp.1-37
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• 2018

잘 알려져 있듯이, 비트겐슈타인은 "논리-철학 논고"에서 러셀의 유형 이론을 명시적으로 비판한다. 그렇다면 러셀의 유형 이론에 대한 비트겐슈타인의 비판의 요점이란 무엇인가? 이 물음에 대답하기 위하여 나는 철학적인 측면과 논리학적인 측면에서 유형 이론을 살펴보고자 한다. "논리-철학 논고"에서 비트겐슈타인의 논리적 구문론은 말하자면 러셀의 유형 이론에 대한 대안이다. 논리적 구문론은 "논리-철학 논고"의 표기법의 기호 규칙들이며 특히 형성 규칙들이다. 비트겐슈타인의 말하기-보이기 구분은 논리적 구문론의 가장 근본적인 근거이다. 비트겐슈타인은 러셀의 유형 이론에 대한 비판과 함께 논리적 문법의 임의성(자의성)과 선험성으로 나아간다. 유형 이론에 대한 이러한 비트겐슈타인의 비판은 결국 프레게와 러셀의 논리학관에 대한 도전이다. 논리학은 세계에 속하는 일반적인 진리나 특성들을 다루지 않으며, 논리학을 이루는 동어반복은 아무것도 말하지 않는다.