Estimation of Actuator Fault Parameters in a Nonlinear Boeing 747 Model Using a Linear Two-Stage Kalman Filter

Abstract

In this paper, an adaptive two-stage linear Kalman filtering algorithm (Wu, Zhang, and Zhou, 2000) is used to estimate the loss of control effectiveness and the magnitude of low degree of stuck faults in a closed-loop nonlinear B747 aircraft. Control effectiveness factors and stuck magnitudes are used to quantify faults entering control systems through actuators. Pseudo random excitation inputs are used to help distinguish partial loss and stuck faults. The partial loss and stuck faults in the stabilizer are identified successfully.