• 제목/요약/키워드: State Estimate

검색결과 1,501건 처리시간 0.033초

Estimating the workability of self-compacting concrete in different mixing conditions based on deep learning

  • Yang, Liu;An, Xuehui
    • Computers and Concrete
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    • 제25권5호
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    • pp.433-445
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    • 2020
  • A method is proposed in this paper to estimate the workability of self-compacting concrete (SCC) in different mixing conditions with different mixers and mixing volumes by recording the mixing process based on deep learning (DL). The SCC mixing videos were transformed into a series of image sequences to fit the DL model to predict the SF and VF values of SCC, with four groups in total and approximately thirty thousand image sequence samples. The workability of three groups SCC whose mixing conditions were learned by the DL model, was estimated. One additionally collected group of the SCC whose mixing condition was not learned, was also predicted. The results indicate that whether the SCC mixing condition is included in the training set and learned by the model, the trained model can estimate SCC with different workability effectively at the same time. Our goal to estimate SCC workability in different mixing conditions is achieved.

State estimation based on fuzzy state transition model

  • Hanazaki, Izumi;Saguchi, Shinichi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.18-23
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    • 1993
  • In this paper, we attempt to estimate the state of a finite state system. In such system, we can observe time series data which has some significant behaviors corresponding to its system states. The behavior is characterized by feature parameters extracted from time series. Our thought is that the system output time series data is expressed as a sequence of behavior patterns which are represented by clusters in feature parameters space. An algorithm jointing fuzzy clustering to fuzzy finite state transition model is suggested.

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An Adaptive Algorithm Applied to a Design of Robust Observer

  • Son, Young-Ik;Hyungbo Shim;Juhoon Back;Jo, Nam-Hoon
    • Journal of Mechanical Science and Technology
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    • 제17권10호
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    • pp.1443-1449
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    • 2003
  • Primary goal of adaptive observers would be to estimate the true states of a plant. Identification of unknown parameters is of secondary interest and is achieved frequently with the persistent excitation condition of some regressors. Nevertheless, two problems are linked to each other in the classical approaches to adaptive observers; as a result, we get a good state estimate once after a good parameter estimate is obtained. This paper focuses on the state estimation without parameter identification so that the state is estimated regardless of persistent excitation. In this direction of research, Besancon (2000) recently summarized that most of adaptive observers in the literature share one common canonical form, in which unknown parameters do not affect the unmeasured states. We enlarge the class of linear systems from the canonical form of (Besancon, 2000) by proposing an adaptive observer (with additional dynamics) that allows unknown parameters to affect those unmeasured states. A recursive algorithm is presented to design the proposed dynamic observer systematically. An example confirms the design procedure with a simulation result.

베이지안 추정법에 의한 소자의 수명 예측에 관한 연구 (A Study on the Lifetime Prediction of Device by the Method of Bayesian Estimate)

  • 오종환;오영환
    • 한국통신학회논문지
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    • 제19권8호
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    • pp.1446-1452
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    • 1994
  • 본 논문은 일반적으로 채택하고 있는 소자(device)의 수명분포인 와이블(Weibull) 분포를 적용하여 소자의 가속(accelerated) 수명 테스트에서 얻은 데이터, 즉 소자의 고정 시간을 이용하여 소자의 수명을 예측(prediction)하는데 필요한 보수(parameter)들을 추정 하는데 베이지안(Bayesian) 추정법을 이용하였다. 베이지안 추정법에서 모수를 추정하기 위해서는 사전정보가 있어야 하는데 본 논문에서는 사전정보 없이 현재의 정보만을 이용하여 모수를 추정하는 방법을 제안하였다. 스트레스가 온도인 경우, Arrhenius 모델을 적용하여 소자의 정상동작 상태에서의 수명을 예측 하는데 선형 추정을 하였다.

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Speed Sensorless DC Motor Using Kalman Filter

  • Whamook, Naramit;Yimman, Surapan;Puangpool, Manoon;Chivapreecha, Sorawat;Dejhan, Kobchai
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.561-564
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    • 2004
  • This paper proposes a new application of Kalman filter to estimate speed sensorless DC motor. Kalman filter can estimate the system state variables accurately; even the system input is disturbed with noise. In the design, the mathematical model of DC motor in discrete state-space form will be created; the speed of DC motor which is considered as state variable and can be estimated by using Kalman filter. In the experiment; TMS320C31 floating point digital signal processor is used for hardware implementation, the input is disturbed with/and without white noise in the experiment. The experimental results show the speed of DC motor which is estimated by Kalman filter has good accuracy when compared with the results from tacho-meter.

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A Particle Filtering Approach for On-Line Failure Prognosis in a Planetary Carrier Plate

  • Orchard, Marcos E.;Vachtsevanos, George J.
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제7권4호
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    • pp.221-227
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    • 2007
  • This paper introduces an on-line particle-filtering-based framework for failure prognosis in nonlinear, non-Gaussian systems. This framework uses a nonlinear state-space model of the plant(with unknown time-varying parameters) and a particle filtering(PF) algorithm to estimate the probability density function(pdf) of the state in real-time. The state pdf estimate is then used to predict the evolution in time of the fault indicator, obtaining as a result the pdf of the remaining useful life(RUL) for the faulty subsystem. This approach provides information about the precision and accuracy of long-term predictions, RUL expectations, and 95% confidence intervals for the condition under study. Data from a seeded fault test for a UH-60 planetary carrier plate are used to validate the proposed methodology.

Clipping Value Estimate for Iterative Tree Search Detection

  • Zheng, Jianping;Bai, Baoming;Li, Ying
    • Journal of Communications and Networks
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    • 제12권5호
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    • pp.475-479
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    • 2010
  • The clipping value, defined as the log-likelihood ratio (LLR) in the case wherein all the list of candidates have the same binary value, is investigated, and an effective method to estimate it is presented for iterative tree search detection. The basic principle behind the method is that the clipping value of a channel bit is equal to the LLR of the maximum probability of correct decision of the bit to the corresponding probability of erroneous decision. In conjunction with multilevel bit mappings, the clipping value can be calculated with the parameters of the number of transmit antennas, $N_t$; number of bits per constellation point, $M_c$; and variance of the channel noise, $\sigma^2$, per real dimension in the Rayleigh fading channel. Analyses and simulations show that the bit error performance of the proposed method is better than that of the conventional fixed-value method.

모드해석과 관측기에 의한 볼스크류 온도분포의 실시간 예측 (Real-time estimation of Temperature Distribution of a Ball Screw System Using Modal Analysis and Observer)

  • 김태훈
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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    • pp.635-640
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    • 2000
  • Thermal deformation of machine tools can be evaluated from the analysis of the whole temperature field. However, it is extremely inefficient and impossible to acquire the whole temperature field by measuring temperatures of every point. So, a temperature estimator, which can estimate the whole temperature field from the temperatures of just a few points, is required. In this paper, 1-dimensional heat transfer problem is modeled with modal analysis and state space equations. and then state observer is designed to estimate the intensity of heat source and the whole temperature field in real-time. The reliability of this estimator is verified by making a comparison between solutions by the proposed method and the exact solutions of examples. The proposed method is applied to the estimation of temperature distribution in a ball screw system.

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DC Motor 제어를 위한 상태궤환 변수의 최적제어 (Optimal control of the State Feedback Variables for Controlling DC Motor)

  • 최진부
    • 대한전자공학회논문지
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    • 제22권3호
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    • pp.31-42
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    • 1985
  • DC motor를 제어하기 위하여, 두개의 feedback sensor 즉, potenfiometer와 tachometer를 사용하고 있다. 최적 제어치를 얻기위한 제어 방법으로써 선형계로써는 kalman regular type, 비 선형계로써는 on-off relay-type와 상태 제환을 적용하였다. 역시, 추적각의 측정 방법으로서는. 측정치를 이웅한 위치와 속도 미분치를 이용한 위치와 속도, 그리고 관측기를 이용한 위치, 속도와 오제곱 분산치를 추정하여 추적각의 제어치를 비교 분석하였다.

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추정오차 저감을 위한 뉴로 관측기 설계 (Design of a Neuro Observer for Reduction of Estimate Error)

  • 남문현;윤광호
    • 대한전기학회논문지:시스템및제어부문D
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    • 제54권5호
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    • pp.285-290
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    • 2005
  • The state observer is being used widely because it has the advantage of the guarantee of reliability on financial problem, over heating, and physical shock. However, an Luenberger observer and a Sliding observer have such problems that an experimenter needs to know dynamics and parameters of the system. And also, the high gain observer has such a problem that it has transient state at the beginning of the observation. In this paper, the Neuro observer is proposed to improve these problems. The proposed Neuro observer complement a problem that occur from increase of gain of High-gain observer in proportion to the square number of observable state variables. And also, the proposed Neuro observer can tune the gain obtained by differentiating observational error at transient state automatically by using the backpropagation training method to stabilize the observational speed. To prove a performance of the proposed observer, it is simulated that the comparison between the state estimate performance of the proposed observer and that of Sliding, High gain observer is made by using a sinusoidal input to the observer which consists of four layers in stable 2nd order system.