Name
Abstract | ||
|---|---|---|
The extended fuzzy Kalman filter (EFKF) of non-linear systems which can deal with fuzzy uncertainty effectively has been developed recently. But it seems to be inapplicable to the cases where the states change abruptly or there exist model mismatches in non-linear systems. Therefore, based on the EFKF, a new concept of the improved fuzzy Kalman filter (IFKF) is proposed in this article. Due to the introduction of the extension orthogonality principle given as a criterion to design the new algorithm, the IFKF can track the abrupt changes of the states and has definite robustness against the model mismatches. Finally, computer simulations with a MIMO non-linear model are presented, which illustrate that the proposed IFKF has the strong tracking ability and robustness against the model mismatches. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1080/00207720903072324 | Int. J. Systems Science |
Keywords | Field | DocType |
definite robustness,improved fuzzy kalman filter,mimo non-linear model,state estimation,non-linear system,new algorithm,extended fuzzy kalman filter,proposed ifkf,new concept,model mismatches,fuzzy uncertainty,kalman filtering,kalman filter,possibility theory,non linear systems,computer simulation | Extended Kalman filter,Alpha beta filter,Fast Kalman filter,Control theory,Robustness (computer science),Kalman filter,Ensemble Kalman filter,Invariant extended Kalman filter,Mathematics,Orthogonality principle | Journal |
Volume | Issue | ISSN |
41 | 5 | 0020-7721 |
Citations | PageRank | References |
4 | 0.48 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| ZhiJie Zhou | 1 | 479 | 37.36 |
| C. H. Chang | 2 | 428 | 36.69 |
| Maoyin Chen | 3 | 241 | 28.51 |
| Huafeng He | 4 | 10 | 0.90 |
| Bang-Cheng Zhang | 5 | 61 | 9.39 |