Two-Stage Kalman Filter Based Estimation of Boeing 747 Actuator/Control Surface Stuck Faults

Abstract

This research aims to construct a two-stage Kalman filter (TSKF) that is available to estimate the control effectiveness of the actuator on behalf of an actuator stuck fault incident occurring on Boeing-747 commercial airplane. The actuator faults can be diagnosed via TSKF that maintains the states and stuck positions or control loss by two section encapsulated estimation algorithms. The performance of the TSKF algorithm is tested. The source of accidents can be as a result from a control surface stuck such an aileron, rudder, elevator; also, it can be present and appear as bird strike that could tear some part of the control surfaces located on the wings or tail of the airplane. In this study, there is a stuck fault on the rudder control surface and the proposed algorithm introduces the value of the stuck of the broken control surface and it is achieved that utilizing TSKF performs satisfying estimation values which are verified as well on lateral dynamics of the airplane.