Optimization of the prefilter in iterative feedback tuning for improved accuracy of the controller parameter update

Author

Hildebrand, Roland ; Lecchini, A. ; Solari, G. ; Gevers, M.

Author_Institution

Center for Oper. Res. & Econ., Univ. Catholique de Louvain, Belgium

Volume

5

fYear

2003

fDate

9-12 Dec. 2003

Firstpage

4422

Abstract

Iterative feedback tuning (IFT) is a data-based method for the tuning of restricted complexity controllers. At each iteration, an update for the parameters of the controller is estimated from data obtained partly from the normal operation of the closed loop system and partly from a special experiment. The choice of a prefilter for the input data to the special experiment is a degree of freedom of the method. In the present contribution, the prefilter is designed in order to enhance the accuracy of the IFT update.

Keywords

closed loop systems; covariance matrices; feedback; optimisation; parameter estimation; tuning; closed loop system; controller parameter; data based method; degree of freedom; iterative feedback tuning; parameter estimation; prefilter design; prefilter optimization; Control systems; Convergence; Cost function; Covariance matrix; Feedback; Iterative methods; Operations research; Optimization methods; Shape; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2003. Proceedings. 42nd IEEE Conference on

ISSN

0191-2216

Print_ISBN

0-7803-7924-1

Type

conf

DOI

10.1109/CDC.2003.1272214

Filename

1272214