Name
Abstract | ||
|---|---|---|
In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light detection and ranging (LIDAR), and inertial measurement unit (IMU) were fused based on the Federal Kalman filter frame. In the filter, the LIDAR estimation fault was detected and isolated, and the disturbance to the drag model was estimated and compensated. Some experiments were carried out, showing that the velocity and position estimation were improved compared with the traditional LIDAR/IMU fusion scheme. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19194337 | SENSORS |
Keywords | Field | DocType |
model-aided navigation,fault-tolerant estimation,improved drag model,quadrotor | Drag,Control theory,Fusion,Kalman filter,Electronic engineering,Angular acceleration,Ranging,Lidar,Fault tolerance,Inertial measurement unit,Engineering | Journal |
Volume | Issue | ISSN |
19 | 19.0 | 1424-8220 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pin Lyu | 1 | 0 | 1.69 |
| Bingqing Wang | 2 | 0 | 0.34 |
| Jizhou Lai | 3 | 3 | 3.78 |
| Shichao Liu | 4 | 0 | 0.34 |
| Zhimin Li | 5 | 0 | 0.34 |