| contributor author | Phan, Minh Q. | |
| contributor author | Vicario, Francesco | |
| contributor author | Longman, Richard W. | |
| contributor author | Betti, Raimondo | |
| date accessioned | 2019-02-28T11:13:26Z | |
| date available | 2019-02-28T11:13:26Z | |
| date copyright | 11/8/2017 12:00:00 AM | |
| date issued | 2018 | |
| identifier issn | 0022-0434 | |
| identifier other | ds_140_03_030902.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4254012 | |
| description abstract | This paper describes an algorithm that identifies a state-space model and an associated steady-state Kalman filter gain from noise-corrupted input–output data. The model structure involves two Kalman filters where a second Kalman filter accounts for the error in the estimated residual of the first Kalman filter. Both Kalman filter gains and the system state-space model are identified simultaneously. Knowledge of the noise covariances is not required. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | State-Space Model and Kalman Filter Gain Identification by a Kalman Filter of a Kalman Filter | |
| type | Journal Paper | |
| journal volume | 140 | |
| journal issue | 3 | |
| journal title | Journal of Dynamic Systems, Measurement, and Control | |
| identifier doi | 10.1115/1.4037778 | |
| journal fristpage | 30902 | |
| journal lastpage | 030902-9 | |
| tree | Journal of Dynamic Systems, Measurement, and Control:;2018:;volume( 140 ):;issue: 003 | |
| contenttype | Fulltext | |