Design of Robust Fault Diagnosis Schemes for a Simulated Aircraft Nonlinear Model

This work describes different procedures for sensor Fault Detection and Isolation (FDI) applied to a simulated model of a commercial aircraft. The main contributions of the paper are related to the design and the optimisation of two FDI schemes based on a linear Polynomial Method (PM) and the NonLinear Geometric Approach (NLGA). The FDI strategies are applied to the aircraft nonlinear model, characterised by tight–coupled longitudinal and lateral dynamics. The capabilities of the residual generators related to the considered FDI techniques are experimentally investigated by simulating a general aircraft reference trajectory. Comparisons with other disturbance decoupling methods for FDI based on Neural Networks (NN) and Unknown Input Kalman Filter (UIKF) are finally reported.