Genetically determined variable structure multiple model estimation

Author

Katsikas, Sokratis K. ; Likothanassis, Spiros D. ; Beligiannis, Gregory N. ; Berkeris, K.G. ; Fotakis, Demetrios A.

Author_Institution

Dept. of Inf. & Commun. Syst., Aegean Univ., Karlovassi, Greece

Volume

49

Issue

10

fYear

2001

fDate

10/1/2001 12:00:00 AM

Firstpage

2253

Lastpage

2261

Abstract

In this paper, the multimodel partitioning theory is combined with genetic algorithms to produce a new generation of multimodel partitioning filters, whose structure varies to conform to a model set being determined dynamically and on-line by using a suitably designed genetic algorithm. The proposed algorithm does not require any knowledge of the model switching law, is practically implementable, and exhibits superior performance compared with a fixed-structure multimodel partitioning filter (MMPF), as indicated by simulation experiments

Keywords

Kalman filters; adaptive estimation; filtering theory; genetic algorithms; parameter estimation; Kalman filter; adaptive estimation; adaptive multimodel partitioning filter; fixed-structure MMPF; genetic algorithms; genetically determined variable structure; multimodel partitioning filters; multimodel partitioning theory; multiple model estimation; performance; simulation experiments; Adaptive filters; Algorithm design and analysis; Filtering algorithms; Filtering theory; Genetic algorithms; Informatics; Kalman filters; Matched filters; Partitioning algorithms; Uncertainty;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.950781

Filename

950781