Control effectiveness estimation using an adaptive Kalman estimator

In this paper, an adaptive Kalman filtering algorithm is exploited for use to estimate the abrupt reduction of control effectiveness in dynamic systems. Control effectiveness factors are used to quantify faults entering control systems through actuators. A set of covariance-dependent forgetting factors is introduced into the filtering algorithm. As a result, the change in the control effectiveness is accentuated to help achieve a more accurate estimate more rapidly. The algorithm is applied to an aircraft model for the identification of impairment in its control surfaces.