Extended Multiple Model Adaptive Estimation for the Detection of Sensor and Actuator Faults

A combination of the multiple model adaptive estimation method (MMAE) with an extended Kalman filter (EKF) is considered. The ability of the MMAE method to detect faults based on a predefined hypothesis and the parameter-estimating ability of an EKF results in a very efficient fault detection approach. This so-called extended multiple model adaptive estimation method (EMMAE) has been investigated on a nonlinear model of an aircraft. The results show that it is a very capable method to detect faults of various types.