Abstract
In this study the innovation approach based model change detection algorithm with multiple system noise scale factors (MSNSF) is proposed. Model of the system with additive changes is considered. It is proved that, the additive changes in system model causes a change in the innovation mean of Kalman filter. For the detection of changes in the innovation mean the MSNSFs are used as the monitoring statistic. Proposed innovation approach based model change detection algorithm with MSNSF is applied for the model of dynamics of an UAV platform. The actuator/surface faults which cause the additive changes in the mathematical model of the UAV are considered. The proposed approach makes it possible to perform the actuator/surface fault detection and isolation operations simultaneously.
| Original language | English |
|---|---|
| Pages (from-to) | 77-82 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| Volume | 51 |
| Issue number | 30 |
| DOIs | |
| Publication status | Published - 2018 |
Bibliographical note
Publisher Copyright:© 2016
Keywords
- Aerospace
- Estimation
- Fault detection
- Fault isolation
- Innovation sequence
- Kalman filters
- Scale factor