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.