| contributor author | Strandt, Andrew | |
| contributor author | Strandt, Alia | |
| contributor author | Yaz, Edwin | |
| date accessioned | 2026-08-23T07:59:19Z | |
| date available | 2026-08-23T07:59:19Z | |
| date copyright | 2026/04/01 | |
| date issued | 2026 | |
| identifier issn | 2689-6117 | |
| identifier other | aldsc-25-1062.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4315909 | |
| description abstract | Abstract. This work introduces a new reduced-order extended Kalman filter (REKF) for discrete nonlinear dynamic systems, which is derived by least-square minimization of the local estimation error covariance. Both the filter and the one-step ahead predictor forms are derived. For demonstration purposes, the REKF is applied to a polynomial nonlinear system, and its estimation error is compared to that of the full-order extended Kalman filter. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | A Reduced-Order Extended Kalman Filter by Local Minimization of the Error Covariance | |
| type | Journal Paper | |
| journal volume | 6 | |
| journal issue | 2 | |
| journal title | ASME Letters in Dynamic Systems and Control | |
| identifier doi | 10.1115/1.4070172 | |
| journal fristpage | 35 | |
| journal lastpage | 45 | |
| page | 11 | |
| tree | ASME Letters in Dynamic Systems and Control:;2026:;volume( 006 ):;issue:002 | |
| contenttype | Fulltext | |
