Fault Diagnosis Strategies for a Simulated Nonlinear Aircraft Model

In this work, different procedures for sensor Fault Detection and Isolation (FDI) applied to a simulated model of a commercial aircraft are presented. The main point of the paper regards the design of two FDI schemes based on a linear Polynomial Method (PM) and the NonLinear Geometric Approach (NLGA). The obtained results highlight a good trade–off between solution complexity and achieved performances. The FDI schemes are applied to the aircraft model, characterised by tight–coupled longitudinal and lateral dynamics. The properties of the residual generators are experimentally investigated and verified by simulating a general aircraft reference trajectory. The overall performance of the developed FDI schemes are analysed in the presence of turbulence, measurement and model errors. Comparisons with other FDI methods based on Neural Networks (NN) and Unknown Input Kalman Filter (UIKF) are finally reported