<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>This paper studies recursive optimal filtering as well as robust fault and state estimation for linear stochastic systems with unknown disturbances. It proposes a new recursive optimal filter structure with transformation of the original system. This transformation is based on the singular value decomposition of the direct feedthrough matrix distribution of the fault which is assumed to be of arbitrary rank. The resulting filter is optimal in the sense of the unbiased minimum-variance criteria. Two numerical examples are given in order to illustrate the proposed method, in particular to solve the estimation of the simultaneous actuator and sensor fault problem and to make a comparison with the existing literature results.</p></abstract>

This paper studies recursive optimal filtering as well as robust fault and state estimation for linear stochastic systems with unknown disturbances. It proposes a new recursive optimal filter structure with transformation of the original system. This transformation is based on the singular value decomposition of the direct feedthrough matrix distribution of the fault which is assumed to be of arbitrary rank. The resulting filter is optimal in the sense of the unbiased minimum-variance criteria. Two numerical examples are given in order to illustrate the proposed method, in particular to solve the estimation of the simultaneous actuator and sensor fault problem and to make a comparison with the existing literature results.

Novel optimal recursive filter for state and fault estimation of linear stochastic systems with unknown disturbances

Research Unit on Control, Monitoring and Safety of Systems (C3S), High School of Sciences and Techniques of Tunis (ESSTT), 5 av. Taha Hussein, BP 56-1008 Tunis, Tunisia

Research Centre in Automation of Nancy (CRAN), Nancy University, CNRS, BP 239, 54506 Vandoeuvre Cedex, France

International Journal of Applied Mathematics and Computer Science

This paper studies recursive optimal filtering as well as robust fault and state estimation for linear stochastic systems with unknown disturbances. It...

Novel optimal recursive filter for state and fault estimation of linear stochastic systems with unknown disturbances

Publié en ligne: 21 déc. 2011

Pages: 629 - 637

DOI: https://doi.org/10.2478/v10006-011-0049-3

Mots clés
Kalman filtering, minimum-variance estimation, state estimation, fault estimation, unknown disturbances, linear discrete-time systems

This content is open access.

Novel optimal recursive filter for state and fault estimation of linear stochastic systems with unknown disturbances

Publié en ligne: 21 déc. 2011

Pages: 629 - 637

DOI: https://doi.org/10.2478/v10006-011-0049-3

Mots clésKalman filtering, minimum-variance estimation, state estimation, fault estimation, unknown disturbances, linear discrete-time systems

This content is open access.

Mots clés
Kalman filtering, minimum-variance estimation, state estimation, fault estimation, unknown disturbances, linear discrete-time systems