• 제목/요약/키워드: Chaos System

검색결과 342건 처리시간 0.023초

Chua다이오드의 비선형제어 (Nonlinear Control of Chua's Diode)

  • 임소영;이호진;이정국;김성열;이금원;이준모
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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    • pp.285-287
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    • 2006
  • The paper treats the nonlinear robust control of Chua's circuit having Chuar's diode as an element based on the internal model principle. The Chua's diode has unknown nonlinear parameters and the circuits parameters are alos assumend unknown. Nonlinear regulator equations are established to obtain 3-fold equilibrium equations on which the output error is zero. Also an internal model of the 3-fold exosystem is constructed for obtaining the control law. Pole Placement method is used for obtaining the feeback control law. Simulation results are presented for tracking the sinusoidal and constant reference input signal. Asymptotic trajectory control and the suppression of chaotic motion in spite of uncertainties in the system are accomplished.

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예술학에 있어서 분석가능성과 인지심리학의 역할 (The Analyzability and the Role of Cognitive Psychology in Science of Art)

  • 박병주
    • 조형예술학연구
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    • 제5권
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    • pp.5-34
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    • 2003
  • This study aims at the observation of some analytical levels-especially those of syntactico-semantical- of the visual expressions in general. As far as the syntactical parts are concerned, there were two steps to be approached. One is to select the paradigms according to the Saussure-Hambidgean suggestions, the other to derive syntagmas from what is called the 'chaos-system', one of nonlinear dynamics. In result, paradigms could be acquired 5 sorts with its so many varieties, as visual templates(VT), supplemented by their reciprocals(R) and complements(CLE), and syntagmas five orbits from each constant c=0 to c=10. In additional, in connection with semantic parts, the study introduced a Gremasian model of discourses and narratives for the interpretation of signifiers. By this, we could cover the conjunctive relationships(+) and the disjunctive(-) of the whole structure of visual expression. Finally, we certified that the above could be fully approved in terms of recent worldly cognitive scientic psychological discoveries.

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Wavelet Neural Network Based Generalized Predictive Control of Chaotic Systems Using EKF Training Algorithm

  • Kim, Kyung-Ju;Park, Jin-Bae;Choi, Yoon-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.2521-2525
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    • 2005
  • In this paper, we presented a predictive control technique, which is based on wavelet neural network (WNN), for the control of chaotic systems whose precise mathematical models are not available. The WNN is motivated by both the multilayer feedforward neural network definition and wavelet decomposition. The wavelet theory improves the convergence of neural network. In order to design predictive controller effectively, the WNN is used as the predictor whose parameters are tuned by error between the output of actual plant and the output of WNN. Also the training method for the finding a good WNN model is the Extended Kalman algorithm which updates network parameters to converge to the reference signal during a few iterations. The benefit of EKF training method is that the WNN model can have better accuracy for the unknown plant. Finally, through computer simulations, we confirmed the performance of the proposed control method.

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최적 TS 퍼지 모델 기반 다중 모델 예측 시스템의 구현과 시계열 예측 응용 (Multiple Model Prediction System Based on Optimal TS Fuzzy Model and Its Applications to Time Series Forecasting)

  • 방영근;이철희
    • 산업기술연구
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    • 제28권B호
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    • pp.101-109
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    • 2008
  • In general, non-stationary or chaos time series forecasting is very difficult since there exists a drift and/or nonlinearities in them. To overcome this situation, we suggest a new prediction method based on multiple model TS fuzzy predictors combined with preprocessing of time series data, where, instead of time series data, the differences of them are applied to predictors as input. In preprocessing procedure, the candidates of optimal difference interval are determined by using con-elation analysis and corresponding difference data are generated. And then, for each of them, TS fuzzy predictor is constructed by using k-means clustering algorithm and least squares method. Finally, the best predictor which minimizes the performance index is selected and it works on hereafter for prediction. Computer simulation is performed to show the effectiveness and usefulness of our method.

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Qi-therapy, chaotic characteristics of peripheral blood pressure and biochemical variables

  • Lee, Myeong-Soo;Rim, Young-Hoon
    • Advances in Traditional Medicine
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    • 제4권3호
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    • pp.215-218
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    • 2004
  • We investigated the effect of Qi therapy (QT) on peripheral blood pressure (PBP), glucose, lactate dehydrogenase (LDH) and cortisol concentrations. Fourteen college students participated in receiving QT and placebo treatment. There were significant differences in embedding dimension of PBP. Plasma cortisol concentrations during QT were significantly lower than during control sessions (P

DC/DC 컨버터의 파라미터 변동에 따른 분기 특성 (Bifurcation Characteristics of DC/DC Converter with Parameter Variation)

  • 오금곤;조금배;김재민;조진섭;정삼용
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 1999년도 전력전자학술대회 논문집
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    • pp.650-654
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    • 1999
  • In this paper, author describe the simulation results concerning the period doubling bifurcation route to chaos of DC/DC boost converter under current mode control to show that it is common phenomena on switching regulator when parameters are improperly chosen or continuously varied beyond the ensured region by system designer. Bifurcation diagrams of periodic orbits of inductor current and capacitor voltage of DC/DC boost converter are plotted with sampled data at moment of each clock pulse causing switching on. DC/DC boost converter studied on this paper is modelled by its state space equations as per switching condition under continuous conduction mode. Current reference signal and capacitance are chosen as the bifurcation parameters and those are varied in step for iterative calculation to find bifurcation points of periodic orbits of state variables.

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요인분석법을 이용한 건설시공 현장에서의 6시그마 개선활동 성공요인에 관한 연구 (A Study on Critical Success Factors for 6 Sigma Project in Construction Site using Factor Analysis)

  • 김채수
    • 상하수도학회지
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    • 제28권1호
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    • pp.125-134
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    • 2014
  • 6 sigma is a management innovation strategy which improves most of all managerial processes including transactional and project based operations such as marketing, purchasing, accounting, and construction. Even though 6 sigma is trying to solve problems from the customer's viewpoint in the scientific manner, project leader feels some difficulties in implementation because of several reasons. Especially the difficulties are prevalent in construction site. This paper investigates the cause of the difficulties through questionnaires, analyzes the investigation results, and verifies the critical success factors of 6 sigma implementation. Factor analysis has been usually employed in reducing quantity of data and summarizing information chaos. In this study, several variables from questionnaires are grouped into just only four factors by the process of factor analysis. The critical success factors are extracted as project management system, implementation mechanism, site condition, and project ownership. Some ideas for each individual success factor are suggested, which are expected to be useful in successful implementation of 6 Sigma in construction site.

패턴분류와 임베딩 차원을 이용한 단기부하예측

  • 최재균;조인호;박종근;김광호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1997년도 하계학술대회 논문집 D
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    • pp.1144-1148
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    • 1997
  • In this paper, a method for the daily maximum load forecasting which uses a chaotic time series in power system and artificial neural network. We find the characteristics of chaos in power load curve and then determine a optimal embedding dimension and delay time. For the load forecast of one day ahead daily maximum power, we use the time series load data obtained in previous year. By using of embedding dimension and delay time, we construct a strange attractor in pseudo phase plane and the artificial neural network model trained with the attractor mentioned above. The one day ahead forecast errors are about 1.4% for absolute percentage average error.

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시계열 데이타의 흔돈도 분석 알고리즘에 관한 연구 (A Study on Complexity Measure Algorithm of Time Series Data)

  • 이병채;정기삼;이명호
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1995년도 춘계학술대회
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    • pp.281-284
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    • 1995
  • This paper describes a complexity measure algorithm based on nonlinear dynamics(chaos theory). In order to quantify complexity or regularity of biomedical signal, this paper proposed fractal dimension-1 and fractal dimension-2 algorithm with digital filter. Approximate entropy algorithm which measure a system regularity are also compared. In this paper investigate what we quantify of biomedical signal. These quantified complexity measure may be a useful information about human physiology.

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Chaotic Dynamics in Tobacco's Addiction Model

  • Bae, Youngchul
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제14권4호
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    • pp.322-331
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    • 2014
  • Chaotic dynamics is an active area of research in biology, physics, sociology, psychology, physiology, and engineering. This interest in chaos is also expanding to the social scientific fields such as politics, economics, and argument of prediction of societal events. In this paper, we propose a dynamic model for addiction of tobacco. A proposed dynamical model originates from the dynamics of tobacco use, recovery, and relapse. In order to make an addiction model of tobacco, we try to modify and rescale the existing tobacco and Lorenz models. Using these models, we can derive a new tobacco addiction model. Finally, we obtain periodic motion, quasi-periodic motion, quasi-chaotic motion, and chaotic motion from the addiction model of tobacco that we established. We say that periodic motion and quasi-periodic motion are related to the pre-addiction or recovery stage, respectively. Quasi-chaotic and chaotic motion are related to the addiction stage and relapse stage, respectively.