Latest-Estimation Based Hierarchical Recursive Extended Least Squares algorithm for ARMAX model
| Autor: | Rui-Qi Dong, Ai-Guo Wu, Shiwei Liu |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Estimation
0209 industrial biotechnology 020901 industrial engineering & automation Computer science 0202 electrical engineering electronic engineering information engineering 020206 networking & telecommunications Algorithm design 02 engineering and technology White noise Recursive extended least squares Algorithm |
| Zdroj: | 2016 35th Chinese Control Conference (CCC). |
| DOI: | 10.1109/chicc.2016.7553096 |
| Popis: | For ARMAX models, a Latest-Estimation Based Hierarchical Recursive Extended Least Squares algorithm is presented in this paper. The basic idea is to make full use of the latest estimation, and combine this with the hierarchical idea. In the proposed algorithm, the estimates of the white noise information vector is updated by using the latest estimation. The convergence performance of the proposed LE-HRELS algorithm is simply analyzed. It is shown by a numerical example that the LE-HRELS algorithm possesses faster convergence speed and higher convergence precision compared with the standard RELS and the HRELS algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|