| Title |
UAV Propeller Fault Detection Using Interacting Multiple Model |
| Authors |
박채훈(Chaehun Park) ; 정철민(Cheolmin Jeong) ; 강창묵(Chang Mook Kang) |
| DOI |
https://doi.org/10.5370/KIEE.2022.71.5.744 |
| Keywords |
Unmanned aerial vehicle; Multirotor aerial vehicle; Fault diagnosis and isolation algorithm; Extended Kalman filter; Interacting multiple model |
| Abstract |
Many studies are being promoted due to the miniaturization of equipment installed in the UAV(Unmanned Aerial Vehicle). Among them, the quadrotor of MAV(Multirotor Aerial vehicle) is the most popular UAV and has been developed in various fields. Practical utilization of UAV requires stable flight or emergency action in fault of UAV parts, but a quadrotor with one motor damaged cannot perform stable flight due to unbalanced force applied to the quadrotor frame. For this reason the development of hexa- or octorotor with more motors is underway and the need to develop FDI(Fault Diagnosis and Isolation) algorithms to use with MAV is increasing. In this paper we designed a simulation based on MAV dynamic and FDI used to classify fault that occurred in the simulation. For fault diagnosis the model based FDI algorithm IMM(Interacting Multiple Model) was applied because the fault affects the system dynamic and output. IMM uses multiple filter models in simultaneously and then compare to the filters estimation and target system output to give weight to suitable filter model. IMM showed accurate and fast fault perceive and classification performance when a fault occurred in the MAV simulation. |