Closed-loop identification using canonical correlation analysis

Author

Chou, C.T. ; Verhaegen, Michel

Author_Institution

Dept. of Electr. Eng., Delft Univ. of Technol., Delft, Netherlands

fYear

1999

fDate

Aug. 31 1999-Sept. 3 1999

Firstpage

311

Lastpage

315

Abstract

We consider the identification of linear state space innovations model from closed-loop data. We suggest to use the subspace closed-loop identification algorithm of [3] to obtain an initial estimate of the deterministic part of the system and then plug this estimate into the second stage of the 2CCA algorithm of Peternell et. al. [9]. The main result of this paper is to show that given closed-loop data and consistent estimates of a number of Markov parameters of the deterministic part of the system, the second stage of the 2CCA algorithm delivers consistent estimates of the system matrices of the innovations model.

Keywords

Markov processes; closed loop systems; correlation methods; identification; linear systems; state-space methods; 2CCA algorithm; Markov parameters; canonical correlation analysis; linear state space innovation model; subspace closed-loop identification algorithm; system matrices; Aerospace electronics; Computational modeling; Data models; Markov processes; Prediction algorithms; Signal processing algorithms; Technological innovation; System identification; closed-loop identification; state space systems; subspace identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (ECC), 1999 European

Conference_Location

Karlsruhe

Print_ISBN

978-3-9524173-5-5

Type

conf

Filename

7099320