Name
Abstract | ||
|---|---|---|
The main contribution of this paper is to design a more accurate optimal/suboptimal fault tolerant state estimator. Federated filters compose of a set of local filters and a master filter, the local filters work in parallel and their solutions are periodically fused by the master filter yielding a global solution. Federated ensemble Kalman filter no reset configuration is developed for multi-sensor data fusion. Ensemble Kalman filter(ENKF) estimation is widely used, where the models are of extremely high order and nonlinear, the initial states are highly uncertain, and a large number of measurements are available. ENKF is used as local filters in federated filter no reset mode design. Fault detection and isolation (FDI) algorithms is applied to local filter's outputs. Faulty local filters are isolated and not fused by master filter to get a fault tolerant filter. Simulation results demonstrate the validity of the proposed filter formation. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/IRI.2013.6642539 | Information Reuse and Integration |
Keywords | Field | DocType |
Kalman filters,fault diagnosis,sensor fusion,ENKF,FDI,fault detection and isolation algorithms,fault tolerant filter,federated ensemble Kalman filter,filter formation,local filters,master filter,multisensor data fusion ensemble Kalman filter,no reset mode design,optimal-suboptimal fault tolerant state estimator,Ensemble Kalman Filter,Fault Detection,Federated Filter,Multi-Sensor Data Fusion | Data mining,Alpha beta filter,Extended Kalman filter,Fast Kalman filter,Control theory,Computer science,Kernel adaptive filter,Adaptive filter,Ensemble Kalman filter,Invariant extended Kalman filter,Filter design | Conference |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maryam Kazerooni | 1 | 1 | 0.36 |
| Faridoon Shabaninia | 2 | 21 | 6.74 |
| Mohammad Vaziri | 3 | 11 | 3.96 |
| Suresh Vadhva | 4 | 12 | 4.36 |