Approximate Input Reconstruction for Diagnosing Aircraft Control Surfaces

An approximate input reconstruction algorithm is used to reconstruct unknown inputs, which are then used for fault detection. The approximate input reconstruction algorithm is a least squares algorithm that estimates both the unknown initial state and input history. The estimated inputs are then compared to the commanded values and sensor values to assess the health of actuators and sensors. This approach is applied to the longitudinal and lateral dynamics of NASA's Generic Transport Model. The input reconstruction algorithm can be used for systems with minimum-phase or nonminimum-phase zeros; however, minimum-phase zeros entail an additional delay in reconstructing inputs, while zeros on the unit circle yield persistent estimation errors and thus poor input reconstruction regardless of the delay.