A Modified k-plane Clustering Algorithm for Identification of Hybrid Systems

Author

Tabatabaei-Pour, Mojtaba ; Salahshoor, Karim ; Moshiri, Behzad

Author_Institution

Dept. of Autom. & Instrum., Pet. Univ. of Technol., Tehran

Volume

1

fYear

0

fDate

0-0 0

Firstpage

1333

Lastpage

1337

Abstract

A new algorithm for the identification of discrete time hybrid systems in the piece-wise affine (PWA) form is introduced. This problem involves the estimation of both the parameters of the affine submodels and the partition of the PWA map from data. At the first stage we propose a modified version of the k-plane clustering algorithm proposed by Bradely and Mangasariang (2000) to provide initial data classification and parameter estimation. Then we apply the refinement algorithm proposed by Bemporad et al. (2003) repeatedly to the estimated clusters in order to improve both the data classification and the parameter estimation

Keywords

discrete time systems; parameter estimation; pattern classification; pattern clustering; refinement calculus; PWA submodel; cluster estimation; data classification; discrete time hybrid system identification; modified k-plane clustering algorithm; parameter estimation; piecewise affine form; refinement algorithm; Automation; Bayesian methods; Clustering algorithms; Control system synthesis; Instruments; Logic; Nonlinear equations; Parameter estimation; Partitioning algorithms; Petroleum; Nonlinear identification; classification; clustering; hybrid systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712564

Filename

1712564