Recursive least-squares estimation for the joint input-state estimation of linear discrete time systems with unknown input

This paper presents a recursive least-squares approach to estimate simultaneously the state and the unknown input of linear time varying discrete time systems with unknown input. The method is based on the assumption that no prior knowledge about the dynamical evolution of the input is available. Th...

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Bibliographic Details
Main Authors: Bessaoudi, T, Khemiri, K, Ben Hmida, Faycal, Gossa, M
Format: Conference Proceeding
Language:English
Subjects:
Covariance matrix
Equations
Information filters
Information formulas
Inversion lemma
least-squares
State estimation
Unknown input estimation
Vectors
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Summary:This paper presents a recursive least-squares approach to estimate simultaneously the state and the unknown input of linear time varying discrete time systems with unknown input. The method is based on the assumption that no prior knowledge about the dynamical evolution of the input is available. The joint input and state estimation are obtained by recursive least-squares formulation by applying the inversion lemmas. The proposed filter is equivalent to recursive three step filter. To illustrate the performance of the proposed filter an example is given.
DOI:10.1109/SSD.2011.5767500