Two subspace algorithms for the identification of combined deterministic-stochastic systems

Author

Van Overschee, Peter ; De Moor, Bart

Author_Institution

Dept. of Electr. Eng., Katholieke Univ., Leuven, Belgium

fYear

1992

fDate

1992

Firstpage

511

Abstract

Two new subspace algorithms for identifying mixed deterministic-stochastic systems are derived. Both algorithms determine state sequences through the projection of input and output data. These state sequences are shown to be outputs of nonsteady-state Kalman filter banks. From these it is easy to determine the state space system matrices. The algorithms are always convergent (noninterative) and numerically stable since they only make use of QR and singular value decompositions. The two algorithms are similar, but the second one trades off accuracy for simplicity. An example involving a glass oven is considered

Keywords

Kalman filters; approximation theory; identification; matrix algebra; state-space methods; stochastic systems; Hankel matrices; combined deterministic-stochastic systems; convergent; glass oven; identification; mixed systems; nonsteady-state Kalman filter banks; numerically stable; singular value decompositions; state sequences; state space system matrices; subspace algorithms; Approximation algorithms; Glass; Iterative algorithms; Matrix decomposition; Observability; Ovens; Singular value decomposition; State-space methods; Stochastic processes; Stochastic systems; System identification; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1992., Proceedings of the 31st IEEE Conference on

Conference_Location

Tucson, AZ

Print_ISBN

0-7803-0872-7

Type

conf

DOI

10.1109/CDC.1992.371682

Filename

371682