Properties of conditional algorithms in restricted complexity set membership identification

Author

Garulli, A. ; Kacewicz, B.Z. ; Vicino, A. ; Zappa, G.

Author_Institution

Dipt. di Ingegneria dell´´Inf., Siena Univ., Italy

Volume

4

fYear

1998

fDate

16-18 Dec 1998

Firstpage

4452

Abstract

Restricted complexity estimation is a major topic in control-oriented identification. Conditional algorithms are used to identify linear finite dimensional models of complex systems, the aim being to minimize the worst-case identification error. High computational complexity of optimal solutions suggests to employ suboptimal estimation algorithms. This paper studies different classes of conditional estimators, and provides results that assess the reliability level of suboptimal algorithms

Keywords

computational complexity; identification; large-scale systems; minimisation; multidimensional systems; reduced order systems; set theory; complex systems; computational complexity; conditional algorithms; control-oriented identification; linear finite dimensional models; reliability; restricted complexity estimation; restricted complexity set membership identification; suboptimal estimation algorithms; worst-case identification error minimization; Additive noise; Computational complexity; Control system synthesis; Estimation error; Informatics; Mathematics; Nonlinear control systems; Nonlinear systems; Topology; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1998. Proceedings of the 37th IEEE Conference on

Conference_Location

Tampa, FL

ISSN

0191-2216

Print_ISBN

0-7803-4394-8

Type

conf

DOI

10.1109/CDC.1998.762016

Filename

762016