An On-line Robust Parameter Identification Algorithm
碩士 === 國立臺灣大學 === 機械工程學研究所 === 98 === This thesis proposes an on-line robust identification algorithm to estimate unknown parameters in a linear regression form that is contaminated by a deterministic disturbance signal. In this thesis, not only the parameters will be obtained by this algorithm...
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ndltd-TW-098NTU054891422019-05-15T20:33:23Z http://ndltd.ncl.edu.tw/handle/q8f9wp An On-line Robust Parameter Identification Algorithm 應用於線上的強韌參數識別演算法 Yi-Je Lin 林逸哲 碩士 國立臺灣大學 機械工程學研究所 98 This thesis proposes an on-line robust identification algorithm to estimate unknown parameters in a linear regression form that is contaminated by a deterministic disturbance signal. In this thesis, not only the parameters will be obtained by this algorithm, but also the disturbance will be estimated by an on-line polynomial fitting model without any disturbance information. In this algorithm, we use a polynomial fitting model with unknown coefficients to represent the disturbance in the system. Both unknown parameters of system and the time-varying disturbance will be estimated accurately by a Kalman filter observer. However, the results of the estimation will be affected by the choice of observer parameters. Under certain circumstances, the singular values of the solution in the Riccati equation will approach infinity. To prevent the singular values from increasing unlimitedly, a threshold for reset is set in order to ensure theis algorithm is capable of successfully estimating the real parameters. 陳明新 2010 學位論文 ; thesis 81 zh-TW |
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碩士 === 國立臺灣大學 === 機械工程學研究所 === 98 === This thesis proposes an on-line robust identification algorithm to estimate unknown parameters in a linear regression form that is contaminated by a deterministic disturbance signal. In this thesis, not only the parameters will be obtained by this algorithm, but also the disturbance will be estimated by an on-line polynomial fitting model without any disturbance information. In this algorithm, we use a polynomial fitting model with unknown coefficients to represent the disturbance in the system. Both unknown parameters of system and the time-varying disturbance will be estimated accurately by a Kalman filter observer. However, the results of the estimation will be affected by the choice of observer parameters. Under certain circumstances, the singular values of the solution in the Riccati equation will approach infinity. To prevent the singular values from increasing unlimitedly, a threshold for reset is set in order to ensure theis algorithm is capable of successfully estimating the real parameters.
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author2 |
陳明新 |
author_facet |
陳明新 Yi-Je Lin 林逸哲 |
author |
Yi-Je Lin 林逸哲 |
spellingShingle |
Yi-Je Lin 林逸哲 An On-line Robust Parameter Identification Algorithm |
author_sort |
Yi-Je Lin |
title |
An On-line Robust Parameter Identification Algorithm |
title_short |
An On-line Robust Parameter Identification Algorithm |
title_full |
An On-line Robust Parameter Identification Algorithm |
title_fullStr |
An On-line Robust Parameter Identification Algorithm |
title_full_unstemmed |
An On-line Robust Parameter Identification Algorithm |
title_sort |
on-line robust parameter identification algorithm |
publishDate |
2010 |
url |
http://ndltd.ncl.edu.tw/handle/q8f9wp |
work_keys_str_mv |
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1719100369186848768 |