Academic Editor: J. Rodellar
Copyright © 2010 Fayçal Ben Hmida et al. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper presents a new robust filter structure to solve the simultaneous state and fault estimation problem of linear
stochastic discrete-time systems with unknown disturbance. The method is based on the assumption that the fault and the
unknown disturbance affect both the system state and the output, and no prior knowledge about their dynamical evolution is
available. By making use of an optimal three-stage Kalman filtering method, an augmented fault and unknown disturbance
models, an augmented robust three-stage Kalman filter (ARThSKF) is developed. The unbiasedness conditions and minimum-variance
property of the proposed filter are provided. An illustrative example is given to apply this filter and to compare it
with the existing literature results.