An innovation-based actuator/surface fault detection, isolation and filter tuning

Purpose: The purpose of the paper is to present an innovation-based new actuator/surface fault detection and isolation (FDI) method, which is sensitive to the changes in the innovation mean of the Kalman filter (KF) and the KF tuning method for the case of actuator/surface failure. Design/methodology/approach: The multiple system noise scale factors (MSNSFs) are used in this method as the monitoring statistics. MSNSFs are determined to make it possible to perform the actuator/surface FDI operations simultaneously. Findings: The introduced FDI algorithm can detect and isolate the loss of effectiveness type actuator/surface faults in real time. The proposed KF tuning method works effectively against actuator/surface fault. The actuator/surface fault detection, isolation and filter tuning are achieved by just using a simple modification over the conventional KF. Originality/value: The MSNSF-based actuator/surface fault detection, isolation and filter tuning algorithms are investigated together for the first time. The actuator/surface FDI operations are performed simultaneously.