Aircraft sensor failure diagnosis using self-organizing fuzzy systems

A novel scheme for diagnosing sensor failures in a flight control system is presented. In the proposed scheme, a set of self-organizing fuzzy systems named as SAFISs are applied as the online approximators for recognizing the sensor outputs in order to determine the failure detection, identification and accommodation (FDIA). SAFIS is an online learning fuzzy system with concurrent structure and parameter learning. The rules of the SAFIS are added or deleted based on the input data without predefining them by trial and error. The efficiency of the proposed scheme is demonstrated by simulation examples where soft failures in the angular rate gyros are successfully diagnosed.