Quadrotor fault detection and isolation based on nonlinear analytical redundancy relations

This paper addresses the analysis and design of a fault detection and isolation scheme (FDI), applied on the quadrotor unmanned air vehicles (UAVs) which is described by a nonlinear model. Using nonlinear analytical redundancy relations (NLARRs) to generate structured residuals. This technique composed by derivatives of known signals to detect and isolate sensor faults by an extended parity space approach. Finally, the results obtained are presented to illustrate the robustness of the proposed scheme.