Title :
Reduced-order Kalman filtering for time-varying systems
Author :
Chandrasekar, J. ; Kim, I.S. ; Bernstein, D.S.
Author_Institution :
Michigan Univ., Ann Arbor
Abstract :
Since the classical Kalman filter provides optimal least- squares estimates of all of the states of a linear time-varying system, there is longstanding interest in obtaining simpler filters that estimate only a subset of states. This objective is of particular interest when the system order is extremely large, which occurs for systems arising from discretized partial differential equations.
Keywords :
Kalman filters; least squares approximations; linear systems; partial differential equations; reduced order systems; time-varying systems; discretized partial differential equations; linear time-varying system; optimal least-squares estimates; reduced-order Kalman filtering; Control systems; Filtering; Kalman filters; Nonlinear filters; Observers; Optimal control; Riccati equations; State estimation; Steady-state; Time varying systems;
Conference_Titel :
Decision and Control, 2007 46th IEEE Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-1497-0
Electronic_ISBN :
0191-2216
DOI :
10.1109/CDC.2007.4434882
