Kalman filter design for control surface failure detection and isolation [flight control]

The use of Kalman filters for residual generation for control surface failure detection and isolation (FDI) is studied. The FDI algorithm investigated consists of two main components: a Kalman filter for residual generation and a set of pairwise log-likelihood-ratio (LLR) tests for decision processing. The performance of several Kalman filter designs under a severe gust level of 20-fps RMS is evaluated. The performance of the FDI algorithm is measured in terms of the probabilities of detection and false alarm which are closely related to the signal-to-noise ratios (SNRs) of the decision LLRs. The filter design process is aided by evaluating the SNRs of the different Kalman filter configurations. It was found that including the gust-shaping filters in the Kalman filter equations improved the FDI performance under severe wind turbulence. However, all the filter configurations evaluated were sensitive to parameter variations