Title :
Optimal Filtering for Linear Systems with Multiple State and Observation Delays
Author :
Basin, Michael ; Martinez-Zuniga, Rodolfo ; Sanchez, Edgar
Author_Institution :
Autonomous Univ. of Nuevo Leon
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
In this paper, the optimal filtering problem for linear systems with multiple state and observation delays is treated proceeding from the general expression for the stochastic Ito differential of the optimal estimate, error variance, and various error covariances. The resulting system of equations for determining the filter gain matrix consists, in the general case, of an infinite set of equations. It is however demonstrated that a finite set of the filtering equations can be obtained in the particular case of equal or commensurable (tauj =qjh, qj are natural) delays in the observation and state equations. In the example, performance of the designed optimal filter for linear systems with state and observation delays is verified against the best Kalman-Bucy filter available for linear systems without delays
Keywords :
delays; differential equations; filtering theory; linear systems; matrix algebra; stochastic systems; Kalman-Bucy filter; differential equations; error covariance; filter gain matrix; filtering equations; linear systems; multiple state delay; observation delay; optimal filtering problem; state equation; stochastic time-delay system; Covariance matrix; Delay estimation; Equations; Filtering; Genetic expression; Indium tin oxide; Linear systems; Nonlinear filters; State estimation; Stochastic systems; Optimal filtering; stochastic time-delay system;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.492