| Título |
Rogust Sensor Fusion Using Federated Kalman Filter and Discrete Generalized-Proportional-Integral Observers |
| Tipo |
Congreso |
| Sub-tipo |
CONACYT |
| Descripción |
Automatic Control and Computer Sciences |
| Resumen |
The federated Kalman filter has been an optimal solution when working with distributed systems providing a global estimation without affecting local filters. Several problems including nonlinearities and high-amplitude noise levels have been tackled to improve the performance of global estimations. In this work, we propose a robust federated Kalman filter composed of a set of discrete generalized-proportional-integral (GPI) observers. We demonstrate how this algorithm yields high-precision estimations by using sensor fusion and active disturbance rejection (ADR) features. The proposed method was compared with other state-of-the-art algorithms where ours had the best performance. © Allerton Press, Inc. 2024. |
| Observaciones |
DOI 10.3103/S0146411624701104 |
| Lugar |
New York |
| País |
Estados Unidos |
| No. de páginas |
630-641 |
| Vol. / Cap. |
v. 58 no.6 |
| Inicio |
2024-12-01 |
| Fin |
|
| ISBN/ISSN |
|
