Multisensor out of sequence data fusion for estimating the state of discrete control systems
The fusion center of a complex control system estimates its state with the information provided by different sensors. Physically distributed sensors, communication networks, pre-processing algorithms, multitasking, etc, introduce non-systematic delays in the arrival of information to the fusion cent...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2009 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/43856 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/43856 |
| Access Level: | acceso abierto |
| Palabra clave: | 004 Tracking Update Informática (Informática) 1203.17 Informática |
| Sumario: | The fusion center of a complex control system estimates its state with the information provided by different sensors. Physically distributed sensors, communication networks, pre-processing algorithms, multitasking, etc, introduce non-systematic delays in the arrival of information to the fusion center, making the information available Out-Of-Sequence (OOS). For real-time control systems, the state has to be efficiently estimated with all the information received so far. So, several solutions of the OOS problem for dynamic Multiple-Input Multiple-Output (MIMO) discrete control systems traditionally solved by the Kalman Filter (KF) have been proposed recently. This paper presents two new streamlined algorithms for the linear and non-linear case. IFAsyn, the linear algorithm, is equivalent to other optimal solutions but more general, efficient and easy to implement. EIFAsyn, the nonlinear one, is a new solution of the OOS problem in the Extended KF (EKF) framework. |
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