Reduction and predictive control design for a computational fluid dynamics model

Author

Astrid, Patricia ; Huisman, Leo ; Weiland, Siep ; Backx, A. C P M

Author_Institution

Dept. of Electr. Eng., Eindhoven Univ. of Technol., Netherlands

Volume

3

fYear

2002

fDate

10-13 Dec. 2002

Firstpage

3378

Abstract

Many models of commercial industrial applications are based on computational fluid dynamics (CFD) models. The models are usually of high order that it becomes infeasible to control or to optimize them. In the paper, it is shown that CFD models can be reduced very effectively by applying proper orthogonal decomposition. The resulting reduced CFD model has a state space structure and therefore enables application of many well-known control designs, including model predictive controllers.

Keywords

computational fluid dynamics; control system synthesis; distributed parameter systems; heat conduction; industrial control; partial differential equations; singular value decomposition; state estimation; temperature control; computational fluid dynamics model; model predictive controllers; model reduction; predictive control design; proper orthogonal decomposition; state space structure; Chemical technology; Computational fluid dynamics; Computational modeling; Computer industry; Control design; Fluid dynamics; Large-scale systems; Partial differential equations; Predictive control; Predictive models;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2002, Proceedings of the 41st IEEE Conference on

ISSN

0191-2216

Print_ISBN

0-7803-7516-5

Type

conf

DOI

10.1109/CDC.2002.1184397

Filename

1184397