Moving horizon state estimation for linear discrete-time singular systems | Zendy

Boulaïd Boulkroune | Zendy; M. Darouach | Zendy; Michel Zasadziński | Zendy

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Moving horizon state estimation for linear discrete-time singular systems

Author(s) -

Boulaïd Boulkroune,

M. Darouach,

Michel Zasadziński

Publication year - 2010

Publication title -

iet control theory and applications

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.059

H-Index - 108

eISSN - 1751-8652

pISSN - 1751-8644

DOI - 10.1049/iet-cta.2008.0280

Subject(s) - kalman filter , estimator , moving horizon estimation , state (computer science) , mathematics , estimation , gaussian , control theory (sociology) , linear system , discrete time and continuous time , horizon , extended kalman filter , computer science , mathematical optimization , algorithm , statistics , engineering , artificial intelligence , mathematical analysis , control (management) , physics , geometry , quantum mechanics , systems engineering

International audienceIn this study, the moving horizon recursive state estimator for linear singular systems is derived from the least squares estimation problem. It will be shown that this procedure yields the same state estimate as the Kalman filter for descriptor systems when the noises are Gaussian. The obtained results are applied to the state and the unknown inputs estimation for discrete-time systems with unknown inputs. A numerical example is presented to illustrate the proposed method

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