In-Flight Monitoring of a Primary Flight Control Electromechanical Actuator⋆

We aim at designing a monitoring algorithm able to perform early detection of degradation that may lead to jamming in the electromechanical actuators (EMAs) used for primary flight control. The challenge is to construct a detection algorithm performing an online monitoring using in-flight data. As the EMAs only move during specific phases of flight, the data subsets containing relevant information for the identification of at least some friction parameters must be determined. This is achieved by using tools from sensitivity analysis. The resulting data analysis is used to govern the parameter estimation part of a Dual Extended Kalman Filter (DEKF) in such a way that all informative data are exploited at best for friction estimation. The method is validated on healthy and faulty synthetic data resulting from a detailed EMA simulator.