Identification of Fault Estimation Filter From I/O Data for Systems With Stable Inversion

• Published in: IEEE transactions on automatic control Vol. 57; no. 6; pp. 1347 - 1361
• Main Authors: Jianfei Dong, Verhaegen, M.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.06.2012; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Additives; Algorithms; Applied sciences; Asymptotic stability; Automatic control; Computer science; control theory; systems; Control system synthesis; Control theory. Systems; Data driven methods; Equations; Estimates; Estimating; Exact sciences and technology; fault estimation; Faults; Inversions; Mathematical analysis; Mathematical model; Modelling and identification; Observers; Stability analysis; Studies; subspace identification; Subspaces; system inversion; unknown input observer; Input output; Unknown input; Control synthesis; Inversion; State space; system inversion; Data driven modelling; Modeling; Direct method; Linear time invariant system; Uncertain system; Covariance; Observer; System identification; Closed loop; unknown input observer; Least squares problem; Subspace method; subspace identification; Regression analysis; State space method; Moving horizon; Unbiased estimation; Filter; Data driven methods; Defect detection; fault estimation

Classical methods for estimating additive faults are based on state-space models, e.g., moving horizon estimation (MHE) and unknown input observers (UIOs). This paper contributes new direct design methods from closed-loop I/O data for systems with stable inversion, which do not require building a st...