• Title, Summary, Keyword: Parameter estimation

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An optimal regularization for structural parameter estimation from modal response

  • Pothisiri, Thanyawat
    • Structural Engineering and Mechanics
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    • v.22 no.4
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    • pp.401-418
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    • 2006
  • Solutions to the problems of structural parameter estimation from modal response using leastsquares minimization of force or displacement residuals are generally sensitive to noise in the response measurements. The sensitivity of the parameter estimates is governed by the physical characteristics of the structure and certain features of the noisy measurements. It has been shown that the regularization method can be used to reduce effects of the measurement noise on the estimation error through adding a regularization function to the parameter estimation objective function. In this paper, we adopt the regularization function as the Euclidean norm of the difference between the values of the currently estimated parameters and the a priori parameter estimates. The effect of the regularization function on the outcome of parameter estimation is determined by a regularization factor. Based on a singular value decomposition of the sensitivity matrix of the structural response, it is shown that the optimal regularization factor is obtained by using the maximum singular value of the sensitivity matrix. This selection exhibits the condition where the effect of the a priori estimates on the solutions to the parameter estimation problem is minimal. The performance of the proposed algorithm is investigated in comparison with certain algorithms selected from the literature by using a numerical example.

Real-Time Identification and Estimation of Transformer Tap Ratios Containing Errors

  • Kim, Hongrae;Kwon, Hyung-Seok
    • KIEE International Transactions on Power Engineering
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    • v.2A no.3
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    • pp.109-113
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    • 2002
  • This paper addresses the issue of parameter error identification and estimation in electric power systems. Parameter error identification and estimation is carried out as a part of the state estimation. A two stage estimation procedure is used to detect and identify parameter errors. Suspected parameters are identified by the WLAV state estimator in the first stage. A new WLAV state estimator adding suspected system parameters in the state vector is used to estimate the exact values of parameters. Supporting examples are given by using the IEEE 14 bus system.

Research for parameter estimation method by basis of Real vehicle data (실차 데이터 기반 차량 파라미터 추정을 위한 기법 연구)

  • Hong T.W.;Park K.;Heo S.J.;Park L.H.;Lee K.W.;Cho Y.J.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • pp.1091-1094
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    • 2005
  • This paper formulates the parameter estimation of cornering behavior of a vehicle. Especially some vehicle parameter is very important on stability control of chassis by ECU, but some parameter is so hard to get by sensor which parameter is included the nonlinear characteristic of tire cornering force. So we need to deduce that parameter from used signal and numerical method. In this study, we propose a estimation method and present the simulation by parameter estimation technique.

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Unknown-Parameter Estimation of Electric-Hydraulic Servo Cylinder Based on Measurements (측정 데이터 기반 전기-유압 서보 실린더의 미지 변수 추정)

  • Seung, Ji Hoon;Yoo, Sung Goo;Seul, Nam O;Noh, Jackyou
    • IEMEK Journal of Embedded Systems and Applications
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    • v.14 no.6
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    • pp.347-353
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    • 2019
  • Electric-hydraulic sever cylinders are used in many offshore applications such as wind energy farms, solar farms and plants. Jack-up barges are often used for these offshore system operations. Jack-up barge control is up/down by hydraulic cylinder position control. Working in harsh environments can lead to changes in internal parameters. This nonlinearity makes precise control difficult. In order to overcome the problems, we proposed a method of unknown-parameter estimation algorithm based on measurements obtained by system. In this paper, we employee Unscented Kalman filter (UKF) to estimate states and unknown-parameter from augmented nonlinear equation. Performance of estimation results is verified in simulation on an environments of Matlab. The estimation results of the state and unknown-parameter show that the estimation error of unknown-parameter is reduced according to decreasing the state estimation error.

Identification of ARMAX Model and Linear Estimation Algorithm for Structural Dynamic Characteristics Analysis (구조동특성해석을 위한 ARMAX 모형의 식별과 선형추정 알고리즘)

  • Choe, Eui-Jung;Lee, Sang-Jo
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.7
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    • pp.178-187
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    • 1999
  • In order to identify a transfer function model with noise, penalty function method has been widely used. In this method, estimation process for possible model parameters from low to higher order proceeds the model identification process. In this study, based on linear estimation method, a new approach unifying the estimation and the identification of ARMAX model is proposed. For the parameter estimation of a transfer function model with noise, linear estimation method by noise separation is suggested instead of nonlinear estimation method. The feasibility of the proposed model identification and estimation method is verified through simulations, namely by applying the method to time series model. In the case of time series model with noise, the proposed method successfully identifies the transfer function model with noise without going through model parameter identification process in advance. A new algorithm effectively achieving model identification and parameter estimation in unified frame has been proposed. This approach is different from the conventional method used for identification of ARMAX model which needs separate parameter estimation and model identification processes. The consistency and the accuracy of the proposed method has been verified through simulations.

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Hybrid navigation parameter estimation from aerial image sequence (항공영상을 이용한 하이브리드 영상 항법 변수 추출)

  • 심동규;정상용;이도형;박래홍;김린철;이상욱
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.2
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    • pp.146-156
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    • 1998
  • Thispapr proposes hybrid navigation parameter estimation using sequential aerial images. The proposed navigation parameter estimation system is composed of two parts: relative position estimation and absolute position estimation. the relative position estimation recursively computes the current velocity and absolute position estimation. The relative position estimation recursively computes the current velocity and position of an aircraft by accumulating navigation parameters extracted from two succesive aerial images. Simple accumulation of parameter values decreases reliability of the extracted parameters as an aircraft goes on navigating. therefore absolute position estimation is required to compensate for position error generated in the relative position step. The absolute position estimation algorithm combining image matching and digital elevation model(DEM) matching is presented. Computer simulation with real aerial image sequences shows the efficiency of the proposed hybrial algorithm.

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The Parameter Estimation of DC-DC Converter by System Identification Method (시스템 식별 기법을 이용한 DC-DC 컨버터 파라메터 추정)

  • Jeon, Jin-Hong;Kim, Tae-Jin;Kim, Kwang-Su;Kim, Kwang-Hwa
    • Proceedings of the KIEE Conference
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    • pp.503-506
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    • 2003
  • In this paper, we present the results of parameter estimation for do-dc converter model by system identification. The parameter estimation for dc-dc converter aims at the diagnosis of its operating status. we applied the system identification method for parameter estimation. For verification of estimated parameter, we compare bode plot of estimated system transfer function and measurement results of HP4194 instrument.

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SPMSM Mechanical Parameter Estimation Using Sliding-Mode Observer and Adaptive Filter (슬라이딩 모드 관측기와 적응 필터를 이용한 SPMSM 기계 파라미터 추정)

  • Kim, Hyoung-Woo;Choi, Joon-Young
    • The Transactions of the Korean Institute of Power Electronics
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    • v.24 no.1
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    • pp.33-39
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    • 2019
  • We propose a mechanical parameter estimation algorithm for surface-mounted permanent magnet synchronous motors (SPMSMs) using a sliding-mode observer (SMO) and an adaptive filter. The SMO estimates system disturbances in real time, which contain the information on mechanical parameters. A desirable feature that distinguishes the proposed estimation algorithm from other existing mechanical parameter estimators is that the adaptive filter estimates electromagnetic torque to improve the estimation performance. Moreover, the SMO acts as a low-pass filter to suppress the chattering effect, which enables the smooth output signals of the SMO. We verify the mechanical parameter estimation performance for SPMSM by conducting extensive experiments for the proposed algorithm.

Parameter Estimation of the Diffusion Model for Demand Side Management Monitoring System (DSM 모니터링을 위한 확산 모형의 계수 추정)

  • Kim, Jin-O;Choi, Cheong-Hun;Kim, Jung-Hoon;Lee, Chang-Ho;Kim, Chang-Seob
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.10
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    • pp.1183-1189
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    • 1999
  • This paper presents the method of parameter estimation of diffusion model for monitoring Demand-Side Management program. Bass diffusion model was applied in this paper, which has different values according to the following parameters; coefficients of innovation, imitation and potential adopters. Though it is very important to estimate three parameters precisely, there has been no empirical way in practice. Thus, this paper presents the method of parameter estimation in case of few data with constraints to reduce the possibility of bad estimation. The constraints can be empirical results or expert's decision. Case studies show the diffusion curves and forecasted values of the peak for the high-efficient lighting. The feedback and nonlinear least-square parameter estimation methods used in this paper enable us to evaluate the status and to predict the effect of DSM program.

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Receding Horizon FIR Parameter Estimation for Stochastic Systems

  • Lee, Kwan-Ho;Han, Soo-Hee;Lee, Changhun;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • pp.159.1-159
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    • 2001
  • A new time-domain FIR parameter estimation called the receding horizon least square estimation (RHLSE) is suggested for stochastic systems by combining the well known least square estimation with the receding horizon strategy. It can be always obtained without the requirement of any \textit{a priori} information about the horizon initial parameter. A fast algorithm for the suggested estimation is also presented which is remarkable in the view of computational advantage and simple implementation. It is shown that the proposed estimation is robust against temporary modeling uncertainties due to their FIR structure through simulation studies.

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