Efficient System Identification of Heterogeneous Distributed Systems via a Structure Exploiting Extended Kalman Filter

Author

Rice, Justin K. ; Verhaegen, Michel

Author_Institution

Delft Center for Syst. & Control, Delft Univ., Delft, Netherlands

Volume

56

Issue

7

fYear

2011

fDate

7/1/2011 12:00:00 AM

Firstpage

1713

Lastpage

1718

Abstract

We consider the problem of computationally efficient system identification of spatially heterogeneous distributed systems. We show how to parametrize distributed interconnected system models such that an extended Kalman Filter can be used for parameter estimation (system identification) in linear computational complexity with respect to the number of subsystems. Furthermore, the identified model will preserve the special sequentially-semi separable (SSS) structure, allowing for the use of efficient structured controller synthesis routines.

Keywords

Kalman filters; computational complexity; interconnected systems; parameter estimation; distributed interconnected system model; extended Kalman Filter; linear computational complexity; parameter estimation; spatially heterogeneous distributed systems; special sequentially semiseparable structure; structured controller synthesis routines; system identification; Artificial neural networks; Computational complexity; Computational modeling; Convergence; Generators; Heating; Special sequentially-semi separable (SSS) structure;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/TAC.2011.2126690

Filename

5729789