• Title/Summary/Keyword: Recursive Parameter Estimation

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Real-time Projectile Motion Trajectory Estimation Considering Air Resistance of Obliquely Thrown Object Using Recursive Least Squares Estimation (비스듬히 던진 물체의 공기저항을 고려한 재귀 최소 자승법 기반 실시간 포물선 운동 궤적 추정)

  • Jeong, Sangyoon;Chwa, Dongkyoung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.3
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    • pp.427-432
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    • 2018
  • This paper uses a recursive least squares method to estimate the projectile motion trajectory of an object in real time. The equations of motion of the object are obtained considering the air resistance which occurs in the actual experiment environment. Because these equations consider air resistance, parameter estimation of nonlinear terms is required. However, nonlinear recursive least squares estimation is not suitable for estimating trajectory of projectile in that it requires a lot of computation time. Therefore, parameter estimation for real-time trajectory prediction is performed by recursive least square estimation after using Taylor series expansion to approximate nonlinear terms to polynomials. The proposed method is verified through experiments by using VICON Bonita motion capture system which can get three dimensional coordinates of projectile. The results indicate that proposed method is more accurate than linear Kalman filter method based on the equations of motion of projectile that does not consider air resistance.

Recursive Parameter estimation algorithm of the Probability (확률밀도함수의 축차모수추정 방법)

  • 한영열;박진수
    • Proceedings of the Korean Institute of Communication Sciences Conference
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    • 1984.04a
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    • pp.42-45
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    • 1984
  • we propose a new parameter estimation algorithm that converge with probability one and in mean square, If the mean is the function of parameter of the probability density function. This recursive algorithm is applicable also ever the parameters we estimate are multiparameter case. And the results are shown by the computer simulation.

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A Dynamic Discount Approach to the Poisson Process

  • Shim, Joo-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.2
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    • pp.271-276
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    • 1997
  • A dynamic discount approach is proposed for the estimation of the Poisson parameter and the forecasting of the Poisson random variable, where the parameter of the Poisson distribution varies over time intervals. The recursive estimation procedure of the Poisson parameter is provided. Also the forecasted distribution of the Poisson random variable in the next time interval based on the information gathered until the current time interval is provided.

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A Study on the Parameter Estimation Algorithm for Nonlinear Systems (비선형 시스템의 계수추정 알고리즘 연구)

  • Lee, Dal-Ho;Seong, Sang-Man
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.7
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    • pp.898-902
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    • 1999
  • In this paper, we proposed an algorithm for estimating parameters of nonlinear continuous-discrete state-space system. This algorithm uses the conventional extended Kalman filter(EKF) for estimating state variables, and modifies the recursive prediction error method for parameter estimation of the nonlinear system. Simulation results for both linear and nonlinear measurements under the environment of process and measurement noises show a convincing performance of the proposed algorithm.

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Online Estimation of Rotational Inertia of an Excavator Based on Recursive Least Squares with Multiple Forgetting

  • Oh, Kwangseok;Yi, Kyong Su;Seo, Jaho;Kim, Yongrae;Lee, Geunho
    • Journal of Drive and Control
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    • v.14 no.3
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    • pp.40-49
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    • 2017
  • This study presents an online estimation of an excavator's rotational inertia by using recursive least square with forgetting. It is difficult to measure rotational inertia in real systems. Against this background, online estimation of rotational inertia is essential for improving safety and automation of construction equipment such as excavators because changes in inertial parameter impact dynamic characteristics. Regarding an excavator, rotational inertia for swing motion may change significantly according to working posture and digging conditions. Hence, rotational inertia estimation by predicting swing motion is critical for enhancing working safety and automation. Swing velocity and damping coefficient were used for rotational inertia estimation in this study. Updating rules are proposed for enhancing convergence performance by using the damping coefficient and forgetting factors. The proposed estimation algorithm uses three forgetting factors to estimate time-varying rotational inertia, damping coefficient, and torque with different variation rates. Rotational inertia in a typical working scenario was considered for reasonable performance evaluation. Three simulations were conducted by considering several digging conditions. Presented estimation results reveal the proposed estimation scheme is effective for estimating varying rotational inertia of the excavator.

A Study on the Recursive Parameter Estimation Density Function Algorithm of the Probability (확률밀도합수의 축차모수추정방식에 관한 연구)

  • 한영렬;박진수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.9 no.4
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    • pp.163-169
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    • 1984
  • We propose a new parameter estimation algorithm that converges with probability one and in mean square, if the mean is the function of parameter of the probability density function. This recursive algorithm is applicable also even though the parameters we estimate are multiparameter case. And the results are shown by the computer simulation.

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An offset-free self-tuning control and an improved recursive parameter estimation, and their application to a real plant

  • 양홍석;이석원
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10a
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    • pp.817-826
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    • 1987
  • An offset-free self-tuning control with pole placement (STCPP) and a recursive parameter estimation with multiple and variable forgetting factors (REWF), together with their application to a real plant, are described. There are two different types of offset-free STCPP; their features are analysed and discussed. REMVF employs as many forgetting factors as parameter estimates. It is suitable when parameters to be estimated are changing at different rates. The offset-free STCPP and REMVF have been successfully applied to a real plant, giving excellent results.

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A Coupled Recursive Total Least Squares-Based Online Parameter Estimation for PMSM

  • Wang, Yangding;Xu, Shen;Huang, Hai;Guo, Yiping;Jin, Hai
    • Journal of Electrical Engineering and Technology
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    • v.13 no.6
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    • pp.2344-2353
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    • 2018
  • A coupled recursive total least squares (CRTLS) algorithm is proposed for parameter estimation of permanent magnet synchronous machines (PMSMs). TLS considers the errors of both input variables and output ones, and thus achieves more accurate estimates than standard least squares method does. The proposed algorithm consists of two recursive total least squares (RTLS) algorithms for the d-axis subsystem and q-axis subsystem respectively. The incremental singular value decomposition (SVD) for the RTLS obtained by an approximate calculation with less computation. The performance of the CRTLS is demonstrated by simulation and experimental results.

A study on the parameter estimate using selective recursive least square (SRLS을 이용한 파라미터 추정에 관한 연구)

  • 유치형;이재하;정찬수
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.441-444
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    • 1989
  • This correspondence presents a recursive estimation algorithm which, unlike conventional ones; updates the estimates only when a sufficient improvement can be obtained with a bounded noise assumption, the resulting sequence of estimates is a sequence of convex sets(ellipsoids) in the parameter space. For the cases studied, the algorithm use less than 20 percent of the. data to update, the estimate and still acquired good accuracy for spectral estimation.

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Estimation of Aerodynamic Coefficients for a Skid-to-Turn Missile using Neural Network and Recursive Least Square (신경회로망과 순환최소자승법을 이용한 Skid-to-Turn 미사일의 공력 파라미터 추정)

  • Kim, Yun-Hwan;Park, Kyun-Bub;Song, Yong-Kyu;Hwang, Ick-Ho;Choi, Dong-Kyun
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.20 no.4
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    • pp.7-13
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    • 2012
  • This paper is to estimate aerodynamic coefficients needed to determine the missiles' controller design and stability from simulation data of Skid-to-Turn missile. Method of determining aerodynamic coefficients is to apply Neural Network and Recursive Least Square and results were compared and researched. Also analysing actual flight test data was considered and sensor noise was added. Estimate parameter of data with sensor noise added and estimated performance and reliability for both methods that did not need initial values. Both Neural Network and Recursive Least Square methods showed excellent estimate results without adding the noise and with noise added Neural Network method showed better estimate results.