Detection of icing and actuators faults in the longitudinal dynamics of small UAVs using an LPV proportional integral unknown input observer

This paper proposes a linear parameter varying proportional integral unknown input observer (PI-UIO) for the diagnosis of actuator faults and icing in unmanned aerial vehicles. It is shown that in presence of sensor noise, the proposed PI-UIO has the advantage of being affected by the noise, but not by its derivative. Another contribution of the paper is the introduction of an icing to wind/noise ratio, which allows performing an optimal tuning of some PI-UIO design parameters. Results obtained with a Zagi Flying Wing simulator are used to validate the effectiveness of the proposed approach.