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Reduced‐order state estimation for linear time‐varying systems
Author(s) -
Kim In Sung,
Teixeira Bruno O. S.,
Chandrasekar Jaganath,
Bernstein Dennis S.
Publication year - 2009
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.141
Subject(s) - estimator , subspace topology , state (computer science) , lyapunov function , algebraic riccati equation , mathematics , control theory (sociology) , discrete time and continuous time , order (exchange) , state estimator , kalman filter , algebraic number , riccati equation , linear system , mathematical optimization , computer science , control (management) , algorithm , nonlinear system , differential equation , statistics , economics , mathematical analysis , artificial intelligence , physics , finance , quantum mechanics
We consider reduced‐order and subspace state estimators for linear discrete‐time systems with possibly time‐varying dynamics. The reduced‐order and subspace estimators are obtained using a finite‐horizon minimization approach, and thus do not require the solution of algebraic Lyapunov or Riccati equations. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society