Identification of linear parameter-varying systems via LFTs

Author

Lee, Lawton H. ; Poolla, Kameshwar

Author_Institution

Dept. of Mech. Eng., California Univ., Berkeley, CA, USA

Volume

2

fYear

1996

fDate

11-13 Dec 1996

Firstpage

1545

Abstract

This paper considers the identification of linear parameter-varying (LPV) systems having linear-fractional parameter dependence. We present a natural prediction error method, using gradient- and Hessian-based nonlinear optimization algorithms to minimize the cost function. Computing the gradients and (approximate) Hessians is shown to reduce to simulating LPV systems and computing inner products. Issues relating to initialization and identifiability are discussed. The algorithms are demonstrated on a numerical example

Keywords

Hessian matrices; minimisation; nonlinear programming; parameter estimation; Hessian-based nonlinear optimization algorithms; LFT; LPV; cost function minimization; gradient-based nonlinear optimization algorithms; identifiability; identification; initialization; linear parameter-varying systems; linear-fractional parameter dependence; prediction error method; 1f noise; Aircraft; Cost function; Linear systems; Mechanical engineering; Missiles; Noise measurement; Noise reduction; Parameter estimation; Time varying systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on

Conference_Location

Kobe

ISSN

0191-2216

Print_ISBN

0-7803-3590-2

Type

conf

DOI

10.1109/CDC.1996.572742

Filename

572742