The main contribution of this paper is a recursive algorithm for parametric system identification in the presence of both noise and model uncertainties. The estimates provided by this algorithm are not invalidated, after a learning period, by the observed input-output data and the assumed system and
โฆ LIBER โฆ
A Method for On-Line Identification of Power System Model Parameters in the Presence of Noise
โ Scribed by Bollinger, K. E.; Khalil, H. S.; Li, L. C. C.; Norum, W. E.
- Book ID
- 117897931
- Publisher
- IEEE
- Year
- 1982
- Tongue
- English
- Weight
- 314 KB
- Volume
- PER-2
- Category
- Article
- ISSN
- 0272-1724
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Recursive system identification in the p
โ
Er-Wei Bai; Roberto Tempo; Krishan Nagpal
๐
Article
๐
1997
๐
Elsevier Science
๐
English
โ 402 KB
Method of measuring signal parameters in
โ
R. M. Pecherskaya; A. V. Shakurskii
๐
Article
๐
1997
๐
Springer US
๐
English
โ 373 KB
Robustness of an arma identification met
โ
P.-E. Gautier; C. Gontier; M. Smail
๐
Article
๐
1995
๐
Elsevier Science
๐
English
โ 551 KB
This paper is concerned with the identification of the modal parameters of structures. It is a well known result that, due to the presence of measurement noise, time domain identification methods often result in biased estimators. Several authors have proposed methods of noise filtering, often based
On-line identification of the parameters
โ
A. Sen; N. K. Sinha; J. D. Wright
๐
Article
๐
1974
๐
John Wiley and Sons
๐
English
โ 274 KB
New approach for the identification of p
โ
S. A. Soliman; S. E. Eman; G. S. Christensen
๐
Article
๐
1990
๐
Springer
๐
English
โ 557 KB
Autocorrelation model-based identificati
โ
Hasan, M.K.; Hossain, N.M.; Naylor, P.A.
๐
Article
๐
2005
๐
The Institution of Electrical Engineers
๐
English
โ 176 KB