Global optimization for identification

Author

Staus, George H. ; Biegler, Lorenz T. ; Ydstie, B. Erik

Author_Institution

Dept. of Chem. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA

Volume

3

fYear

1997

fDate

10-12 Dec 1997

Firstpage

3010

Abstract

The formulation of the transfer function identification problem leads directly to a nonlinear optimization problem. This nonlinear optimization problem is non-convex and may exhibit many local optima. As a result of the presence of local optimum, optimization methods based upon gradient techniques cannot be guaranteed to converge to the global optimum. A relaxation branch and bound technique is proposed to solve the problem. The algorithm is presented and its convergence properties discussed. Finally, several simulation examples utilizing the global technique are provided

Keywords

convergence of numerical methods; identification; quadratic programming; relaxation theory; transfer functions; branch and bound; convergence; global optimization; identification; local optima; nonlinear optimization; quadratic programming; relaxation; transfer function; Equations; Least squares approximation; Linear approximation; Optimization methods; Polynomials; Power system modeling; Signal processing; Statistical analysis; Transfer functions; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1997., Proceedings of the 36th IEEE Conference on

Conference_Location

San Diego, CA

ISSN

0191-2216

Print_ISBN

0-7803-4187-2

Type

conf

DOI

10.1109/CDC.1997.657910

Filename

657910