Name
Title | ||
|---|---|---|
Hierarchical recursive least squares parameter estimation of non-uniformly sampled Hammerstein nonlinear systems based on Kalman filter. |
Abstract | ||
|---|---|---|
This paper focuses on parameter estimation problems for non-uniformly sampled Hammerstein nonlinear systems. By combining the lifting technique and state space transformation, we derive a nonlinear regression identification model with different input and output updating rates. Furthermore, the unmeasurable state vector is estimated by Kalman filter, and by using the hierarchical identification principle, we develop a hierarchical recursive least squares algorithm for estimating the unknown parameters of the identification model. Finally, illustrative examples are given to indicate that the proposed algorithm is effective. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.jfranklin.2017.02.010 | Journal of the Franklin Institute |
Field | DocType | Volume |
Mathematical optimization,State vector,Nonlinear system,Control theory,Nonlinear regression,Kalman filter,Input/output,Estimation theory,State space,Mathematics,Recursive least squares filter | Journal | 354 |
Issue | ISSN | Citations |
10 | 0016-0032 | 3 |
PageRank | References | Authors |
0.40 | 15 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lincheng Zhou | 1 | 27 | 3.92 |
| Xiangli Li | 2 | 3 | 0.40 |
| Lijie Shan | 3 | 3 | 0.40 |
| Jing Xia | 4 | 66 | 11.85 |
| Wei Chen | 5 | 1711 | 246.70 |