Title :
A new filtering method for linear singularly perturbed systems
Author :
Gajic, Z. ; Lim, M.T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA
fDate :
9/1/1994 12:00:00 AM
Abstract :
In this paper we present a new method which allows complete decomposition of the optimal global Kalman filter for linear singularly perturbed systems into pure-slow and pure-fast local optimal filters both driven by the system measurements. The method is based on the exact decomposition of the global singularly perturbed algebraic Riccati equation into pure-slow and pure-fast local algebraic Riccati equations. An F-8 aircraft example demonstrates the proposed method
Keywords :
Kalman filters; filtering and prediction theory; perturbation techniques; F-8 aircraft; decomposition; linear singularly perturbed systems; local algebraic Riccati equations; optimal global Kalman filter; pure-fast local optimal filters; pure-slow local optimal filters; Aircraft; Communication channels; Coordinate measuring machines; Filtering theory; Gain measurement; Matrix decomposition; Noise measurement; Nonlinear filters; Riccati equations; Technological innovation;
Journal_Title :
Automatic Control, IEEE Transactions on
