• 제목/요약/키워드: State Estimator

검색결과 309건 처리시간 0.03초

Variance components estimation in the presence of drift

  • Kim, Jaehee;Ogden, Todd
    • Communications for Statistical Applications and Methods
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    • 제23권1호
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    • pp.33-45
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    • 2016
  • Variance components should be estimated based on mean change when the mean of the observations drift gradually over time. Consistent estimators for the variance components are studied for a particular modeling situation with some underlying functions or drift. We propose a new variance estimator with Fourier estimation of variations. The consistency of the proposed estimator is proved asymptotically. The proposed procedures are studied and compared empirically with the variance estimators removing trends. The result shows that our variance estimator has a smaller mean square error and depends on drift patterns. We estimate and apply the variance to Nile River flow data and resting state fMRI data.

공정평균을 관리하기 위한 로버스트 관리도 (Robust Control Chart for the Control of the Process Mean)

  • 이병근;정현석;남호수
    • 산업경영시스템학회지
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    • 제21권48호
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    • pp.65-71
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    • 1998
  • Control chart is a very extensively used tool in testing whether a process is in a state of statistical control or not. In this paper, a robust control chart for variables is proposed, which is based on the Huber's M-estimator. The Huber's M-estimator is a well-known robust estimator in sense of distributional robustness. In the proposed chart, the estimation of the process deviation is modified to have a stable level and high power. To compare the performances of the proposed control chart with the classical (equation omitted), some Monte Carlo simulations are performed. The simulation results show that the robust control chart has good performance.

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외란 추정기를 이용한 유연 매니퓰레이터의 선단 위치제어 (Tip Position Control of Flexible Manipulator Using Disturbance Estimator)

  • 김상열;최승복
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2001년도 추계학술대회논문집 I
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    • pp.219-224
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    • 2001
  • An accurate tip position control of a single-link flexible manipulator subjected to torque disturbance is achieved by utilizing so called sliding mode controller with disturbance estimation (SMCDE). After formulating the governing equation of motion in the state 1pace representation, a stable sliding surface is designed via the LQR method. The SMCDE is then synthesized by integrating equivalent sliding mode controller with the disturbance estimator which is featured by an integrated average value of the imposed disturbance over a certain sampling period. The regulating tip motion of the flexible manipulator is evaluated by employing the proposed SMCDE.

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시각장애인을 위한 위치 및 헤딩 추정 시스템 연구 (Position and Heading Estimation System for the Visually Impaired Person)

  • 최가형;천효석;박진배;윤태성
    • 전기학회논문지
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    • 제62권3호
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    • pp.387-394
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    • 2013
  • A travel aid system for the visually impaired person is proposed by providing the position and heading information. The position and heading information is obtained from range difference localization estimator, and the information is notified to the visually impaired person by using braille display system. For the precise estimation of the position and heading information, we apply recently developed linear localization estimator which utilizes the instrumental variable method and the state augmentation method. The estimation results are compared with well-known Kalman filter through experiment.

Online Probability Density Estimation of Nonstationary Random Signal using Dynamic Bayesian Networks

  • Cho, Hyun-Cheol;Fadali, M. Sami;Lee, Kwon-Soon
    • International Journal of Control, Automation, and Systems
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    • 제6권1호
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    • pp.109-118
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    • 2008
  • We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.

신경망 기법을 이용한 스튜어트 플랫폼의 순기구학 추정 (The Estimation for the Forward Kinematic Solution of Stewart Platform Using the Neural Network)

  • 이형상;한명철;이민철
    • 한국정밀공학회지
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    • 제16권8호
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    • pp.186-192
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    • 1999
  • This paper introduces a study of a method for the forward kinematic analysis, which finds the 6 DOF motions and velocities from the given six cylinder lengths in the Stewart platform. From the viewpoints of kinematics, the solution for the inverse kinematic is easily found by using the vectors of the links which are composed of the joint coordinates in base and plate frames, to act contrary to the serial manipulator, but forward kinematic is difficult because of the nonlinearity and complexity of the Stewart platform dynamic equation with the multi-solutions. Hence we, first in this study, introduce the linear estimator using the Luenberger's observer, and the estimator using the nonlinear measured model for the forward kinematic solutions. But it is difficult to find the parameter of the design for the estimation gain or to select the estimation gain and the constant steady state error exists. So this study suggests the estimator with the estimation gain to be learned by the neural network with the structure of multi-perceptron and the learning method using back propagation and shows the estimation performance using the simulation.

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로버스트 지수가중 이동평균(EWMA) 관리도 (A Robust EWMA Control Chart)

  • 남호수;이병근;주철민
    • Journal of the Korean Data and Information Science Society
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    • 제10권1호
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    • pp.233-241
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    • 1999
  • 본 논문에서는 공정평균을 관리하기 위한 관리도로서 지수가중 이동평균(EWMA)관리도를 고려하였다. 기존의 표본평균에 기초한 관리도의 비로버스트성 (non-robustness)에 근거하여 공정평균의 로버스트 추정량인 M-추정량에 기초한 지수가중 이동평균 관리도를 제안하였다. 제안된 관리도의 성능을 기존의 관리도와 비교해 보기 위하여 다양한 상황에서 모의실험을 행하였으며, 실험결과 제안된 관리도의 우수성이 입증되었다.

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Experimental validation of Kalman filter-based strain estimation in structures subjected to non-zero mean input

  • Palanisamy, Rajendra P.;Cho, Soojin;Kim, Hyunjun;Sim, Sung-Han
    • Smart Structures and Systems
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    • 제15권2호
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    • pp.489-503
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    • 2015
  • Response estimation at unmeasured locations using the limited number of measurements is an attractive topic in the field of structural health monitoring (SHM). Because of increasing complexity and size of civil engineering structures, measuring all structural responses from the entire body is intractable for the SHM purpose; the response estimation can be an effective and practical alternative. This paper investigates a response estimation technique based on the Kalman state estimator to combine multi-sensor data under non-zero mean input excitations. The Kalman state estimator, constructed based on the finite element (FE) model of a structure, can efficiently fuse different types of data of acceleration, strain, and tilt responses, minimizing the intrinsic measurement noise. This study focuses on the effects of (a) FE model error and (b) combinations of multi-sensor data on the estimation accuracy in the case of non-zero mean input excitations. The FE model error is purposefully introduced for more realistic performance evaluation of the response estimation using the Kalman state estimator. In addition, four types of measurement combinations are explored in the response estimation: strain only, acceleration only, acceleration and strain, and acceleration and tilt. The performance of the response estimation approach is verified by numerical and experimental tests on a simply-supported beam, showing that it can successfully estimate strain responses at unmeasured locations with the highest performance in the combination of acceleration and tilt.

Estimation of Parameters of a Two-State Markov Process by Interval Sampling

  • Jang, Joong-Soon;Bai, Do-Sun
    • 한국경영과학회지
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    • 제6권2호
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    • pp.57-64
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    • 1981
  • This paper develops a method of modifying the usual maximum likelihood estimators of the parameters of a two state Markov process when the trajectory of the process can only he observed at regular epochs. The method utilizes the limiting behaviors of the process and the properties of state transition counts. An efficient adaptive strategy to be used together with the modified estimator is also proposed. The properties of the new estimators and the adaptive strategy are investigated using Monte Carlo simulation.

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가중최소절대값을 이용한 변압기 텝 추정 알고리즘 (An Algorithm for Transformer Tap Estimation by WLAV State Estimator)

  • 김홍래;권형석
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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    • pp.279-281
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    • 1999
  • This paper addresses the issues of the parameter error detection and identification in power system. The parameter error identification is carried out as part of the state estimation procedure. The weighted least absolute value(WLAV) estimation method is used for this procedure. The standard formulation of the state estimation problem is modified to include the effects of the parameter errors as well. A two step procedure for the detection and identification of faulted parameters is proposed. Supporting examples are given using IEEE 14 bus system.

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