Identification of linear systems: a general framework for the theory

Author

Deistler, Manfred

Author_Institution

Inst. fur Okonometrie, Oper. Res. und Systemtheorie, Tech. Univ. Wien, Austria

Volume

3

fYear

1999

fDate

1999

Firstpage

2822

Abstract

A general framework for the theory of identification of linear, time-invariant, stable and finite-dimensional systems is presented. The emphasis is on state space forms. The first part deals with parameter spaces and the relation between transfer functions and parameters. Full parametrizations, canonical forms, overlapping descriptions and local coordinates are considered. In the second part estimation for given dynamic specification is treated. Maximum likelihood type estimators and subspace identification procedures are discussed with an emphasis on asymptotic properties. The third part deals with order estimation

Keywords

identification; linear systems; maximum likelihood estimation; multidimensional systems; stability; transfer functions; asymptotic properties; canonical forms; finite-dimensional systems; linear systems identification; local coordinates; maximum likelihood estimators; order estimation; overlapping descriptions; parameter spaces; parametrizations; stable systems; state space forms; subspace identification procedures; time-invariant systems; transfer functions; Eigenvalues and eigenfunctions; Joining processes; Linear systems; Maximum likelihood estimation; Operations research; Parameter estimation; Stability; State-space methods; Transfer functions; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1999. Proceedings of the 38th IEEE Conference on

Conference_Location

Phoenix, AZ

ISSN

0191-2216

Print_ISBN

0-7803-5250-5

Type

conf

DOI

10.1109/CDC.1999.831361

Filename

831361