Orthonormal basis selection for LPV system identification, the Fuzzy-Kolmogorov c-Max approach

Author

Tóth, R. ; Heuberger, P.S.C. ; Van den Hof, P.M.J.

Author_Institution

Delft Center for Syst. & Control, Delft Univ. of Technol.

fYear

2006

fDate

13-15 Dec. 2006

Firstpage

2529

Lastpage

2534

Abstract

A fuzzy clustering approach is developed to select pole locations for orthonormal basis functions (OBFs), used for identification of linear parameter varying (LPV) systems. The identification approach is based on interpolation of locally identified linear time invariant (LTI) models, using globally fixed OBFs. Selection of the optimal OBF structure, that guarantees the least worst-case local modelling error in an asymptotic sense, is accomplished through the fusion of the Kolmogorov n-width (KnW) theory and fuzzy c-means (FcM) clustering of observed sample system poles

Keywords

fuzzy systems; linear systems; pattern clustering; time-varying systems; Kolmogorov n-width theory; fuzzy c-means clustering; fuzzy-Kolmogorov c-max approach; linear parameter varying system; linear time invariant model; orthonormal basis function; Control design; Control systems; Electrical equipment industry; Finite impulse response filter; Fuzzy control; Fuzzy systems; Interpolation; System identification; Time varying systems; USA Councils;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2006 45th IEEE Conference on

Conference_Location

San Diego, CA

Print_ISBN

1-4244-0171-2

Type

conf

DOI

10.1109/CDC.2006.377063

Filename

4177378