Hybrid Fault Detection and Isolation Method for UAV Inertial Sensor Redundancy Management System
| Authors: | Kim Youdan, Seoul National University, Korea, Republic of
Kim Hyoung Seok, Seoul National University, Korea, Republic of
Park Sang Kyun, Seoul National University, Korea, Republic of
Park Chan Gook, Seoul National University, Korea, Republic of |
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| Topic: | 7.3 Aerospace |
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| Session: | Unmanned Aerial Vehicles |
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| Keywords: | Fault Detection and Isolation, Inertial Sensor, Unscented Kalman Filter, UAV, Hardware Redundancy, Analytic Redundancy |
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Abstract
Redundant system with three 2-DOF inertial sensors is one of the possible candidates for UAV inertial sensor redundancy management system. In the conventional fault detection and isolation (FDI) techniques using hardware redundancy, at least four 2-DOF inertial sensors are needed to detect and isolate the faulty sensor. Since two input axes of 2-DOF inertial sensors are mechanically correlated with each other, the fault of one axis sensor can affect the fault of the other axis sensor. Therefore, the study of multiple FDI technique is required to deal with this problem. In this study, a hybrid FDI technique is proposed for multiple FDI. The proposed FDI algorithm is based on hardware redundancy and is combined with an analytic redundancy by utilizing the unscented Kalman Filter. Numerical simulations are performed to verify the effectiveness of the proposed FDI technique
