• Title/Summary/Keyword: Fuzzy continuous

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Development of Fuzzy Objective Functioin for Establishing the Region Correspondence

  • Soh, Young-sung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.2 no.3
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    • pp.22-28
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    • 1992
  • One of the challenging problems in dynamic scene analysis is the correspondence problem. Points and lines have been two major entities for establishing the correspondence among suxcessive frmes and gave rise to discrete approach to dynamic scene analysis. SOme researchers take continuous approach to analyse the motion. There it is usually assumed that some sort of region correspondence has already been established. In this paper, we propose a method based on fuzzy membership function for solving region correspondence problem.

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Adaptive Fuzzy Controller with Variable Deadzone (가변 사구간을 갖는 적응 퍼지 제어기)

  • 구근모
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.03a
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    • pp.39-42
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    • 1998
  • This paper proposes an adaptive fuzzy control scheme for a class of continuous-time nonlinear dynamic systems for which an explicit linear parameterization of the uncertainty is either unknown or impossible. In order to improve robustness under approximation errors and disturbances the proposed scheme includes deadzone in adaptation laws which varies its size adaptively. The assumption of known bounds on the approximation errors and disturbances is not required since those are estimated using adaptation laws. The overall adaptive scheme is proven to guarantee uniform ultimate boundedness in the Lyapunov sense.

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Digital Fuzzy Control of Nonlinear Systems Using Intelligent Digital Redesign

  • Lee, Ho-jae;Kim, Hag-bae;Park, Jin-bae;Cha, Dae-bum;Joo, Young-hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.7
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    • pp.621-627
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    • 2001
  • In this paper, a novel and efficient global intelligent digital redesign technique for a Takagi-Sugeno (TS) fuzzy system is addressed. The proposed method should be notably discriminated from the previous works in that in allows us to globally match the states of the closed-loop TS fuzzy system with the pre-designed continuous-time fuzzy-model-based controller and those with the digitally redesigned fuzzy-model-based controller, and further to guarantee the stabilizability by the redesigned controller in the sense of Lyapunov. Sufficient conditions for the global state-matching and the stability of the digitally controller system are formulated in terns of linear matrix inequalities (LMIs). The Duffing-like chaotic oscillator is simulated and demonstrated, to validate the effectiveness of the proposed digital redesign technique, which implies the safe applicability to the digital control system.

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A fuzzy model of human performance for VDU workers (VDU작업자의 작업수행도에 대한 퍼지모형)

  • ;;;神代雅晴
    • Journal of the Ergonomics Society of Korea
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    • v.14 no.1
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    • pp.97-104
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    • 1995
  • The widespread use of VDU has improved the efficiency of information transmission between man and machine, but has caused new occupational health and ergonomics problems. In this study, we tried to construct a fuzzy hyman performance model of VDU workers in Korea. Fuzzy inferences of human perfor- mance are obtained from the fuzzy inference rule with the job difficulty, CFF, SACL, Type A. and the degree of concentration in VDU work. Eight healthy female undergraduate students at Kyungnam university for subjects aged 20 to 23 years were examined in this experiment. They calculated continuous addition, subtraction, and multiplication of 1 or 2 digit numbers that were produced randomly on the CRT. Subjects peoformed two types of a numeric operation, which easy and difficult work produced 400 and 600 problems within a 40 minute work session, respectively. Subjects were tested over two workdays according to the type of work(easy and difficult) consisting of four 40 minutes work sessions in the morning. Each work lasted for five minutes with a ten minutes rest break. 117 fuzzy inference rules were obtained from the experimental data. The value of consequent part was obtained by a descent method. The difference between real human error and estimated value of fuzzy inference was $1.8075{\pm}1.8591%(M{\pm}SD)$. The difference in easy and diffcult works were $2.69{\pm}2.13%$ and $0.92{\pm}0.93%$, respectively.

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Terminal Sliding Mode Control Using One Dimensional Fuzzy Rule Type Sliding Surfaces (일차원 퍼지 규칙 슬라이딩 평면을 이용한 터미널 슬라이딩 모드 제어)

  • Seo, Sam-Jun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.5
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    • pp.402-408
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    • 2016
  • In this paper, a new approach to the terminal sliding mode control using adaptive fuzzy sliding surfaces is proposed. The idea behind this approach is to utilize an adaptive sliding surface, in which the slope of the surface is updated on line using a SISO fuzzy logic inference system. We expanded the concepts of terminal sliding mode controller and proposed the terminal sliding mode control input with continuous reaching laws. The computer simulation results have shown the improved performance of the proposed control approach in terms of a decrease in the reaching and settling times and chattering free as compared to the conventional terminal sliding mode control with a fixed sliding surface. The proposed controller has also an advantage that has less computational burden to the conventional terminal sliding mode control using one-directional fuzzy rules.

Mobile Client-Server System for Real-time Continuous Query of Moving Objects

  • Kim, Young-Choon;Joo, Hae-Jong;Kim, Young-Baek;Rhee, Sang-Yong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.2
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    • pp.95-102
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    • 2011
  • In this paper, a Mobile Continuous Query Processing System (MCQPS) is designed to solve problems related to database hoarding, maintenance of shared data consistency, and optimization of logging. These problems are caused by weak connectivity and disconnection of wireless networks inherent in mobile database systems under mobile client-server environments. We show the superiority of the proposed MCQPS by comparing its performance to the Client-Intercept-Server (C-I-S) model. In addition, several experimental results show the effectiveness of our proposed indexing structure and methodology for real-time continuous queries.

Derivation of a Linear PID Control Law from a Fuzzy Control Theory (퍼지 제어기로부터 PID 제어기의 구현에 관한 연구)

  • 최병재;김병국
    • Journal of the Korean Institute of Intelligent Systems
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    • v.7 no.2
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    • pp.70-78
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    • 1997
  • Proportional-integral-derivative(P1D) controllers have been still widely used in industrial processes due to their simplicity, effectiveness, robustness for a wide range of operating conditions, and the familiarity of control engineers. And a number of recent papers in fuzzy systems are showing that fuzzy systems are universal approximators. That is, fuzzy controllers are capable of approximating any real continuous function on a compact set of arbitrary accuracy. In this paper, we derive the linear PID control law from the fuzzy control algorithm where all fuzzy sets for representing plant state variables and a control variable use common triangular types. We first lead a linear PD control law from a fuzzy logic control with only two fuzzy sets for error and change-of-error. And then we derive the linear PID control law from a fuzzy controller. We here assumed that the intervals of error, change-of-error, and integral error could be partitioned into arbitrary numbers, respectively. As a result, a linear PID controller is only a sort of various fuzzy logic controls.

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Learning Distribution Graphs Using a Neuro-Fuzzy Network for Naive Bayesian Classifier (퍼지신경망을 사용한 네이브 베이지안 분류기의 분산 그래프 학습)

  • Tian, Xue-Wei;Lim, Joon S.
    • Journal of Digital Convergence
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    • v.11 no.11
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    • pp.409-414
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    • 2013
  • Naive Bayesian classifiers are a powerful and well-known type of classifiers that can be easily induced from a dataset of sample cases. However, the strong conditional independence assumptions can sometimes lead to weak classification performance. Normally, naive Bayesian classifiers use Gaussian distributions to handle continuous attributes and to represent the likelihood of the features conditioned on the classes. The probability density of attributes, however, is not always well fitted by a Gaussian distribution. Another eminent type of classifier is the neuro-fuzzy classifier, which can learn fuzzy rules and fuzzy sets using supervised learning. Since there are specific structural similarities between a neuro-fuzzy classifier and a naive Bayesian classifier, the purpose of this study is to apply learning distribution graphs constructed by a neuro-fuzzy network to naive Bayesian classifiers. We compare the Gaussian distribution graphs with the fuzzy distribution graphs for the naive Bayesian classifier. We applied these two types of distribution graphs to classify leukemia and colon DNA microarray data sets. The results demonstrate that a naive Bayesian classifier with fuzzy distribution graphs is more reliable than that with Gaussian distribution graphs.

Fire-Flame Detection using Fuzzy Finite Automata (퍼지 유한상태 오토마타를 이용한 화재 불꽃 감지)

  • Ham, Sun-Jae;Ko, Byoung-Chul
    • Journal of KIISE:Software and Applications
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    • v.37 no.9
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    • pp.712-721
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    • 2010
  • This paper proposes a new fire-flame detection method using probabilistic membership function of visual features and Fuzzy Finite Automata (FFA). First, moving regions are detected by analyzing the background subtraction and candidate flame regions then identified by applying flame color models. Since flame regions generally have continuous and an irregular pattern continuously, membership functions of variance of intensity, wavelet energy and motion orientation are generated and applied to FFA. Since FFA combines the capabilities of automata with fuzzy logic, it not only provides a systemic approach to handle uncertainty in computational systems, but also can handle continuous spaces. The proposed algorithm is successfully applied to various fire videos and shows a better detection performance when compared with other methods.

Intelligent Digital Redesign for Uncertain Nonlinear Systems Using Power Series (Powrer Series를 이용한 불확실성을 갖는 비선형 시스템의 지능형 디지털 재설계)

  • Sung Hwa Chang;Park Jin Bae;Go Sung Hyun;Joo Young Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.7
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    • pp.881-886
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    • 2005
  • This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent tile complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of tile digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.