HYBRID FAULT DETECTION AND ISOLATION METHOD FOR UAV INERTIAL SENSOR REDUNDANCY MANAGEMENT SYSTEM

Abstract

Redundant system with three two-degree-of-freedom (2-DOF) inertial sensors is one of the possible candidates for the UAV inertial sensor redundancy management system. In the conventional 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. When three sensors are used, singular direction problem can be occurred in detecting process, where false alarm may be declared such that two sensors have bias fault although only one sensor is out of order. Therefore, the study of multiple fault detection and isolation (FDI) technique is required to deal with these problems. In this study, a hybrid FDI technique is proposed for multiple FDI of three 2-DOF sensor system. 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.