Warm start of the primal-dual interior point method for process monitoring

Author

Chen, Changan ; Kantor, Jeffrey C.

Author_Institution

Dept. of Chem. Eng., Notre Dame Univ., IN, USA

Volume

5

fYear

1997

fDate

4-6 Jun 1997

Firstpage

2955

Abstract

In this work, a data-based fault detection is formulated as a constrained optimization problem. It is then converted to a linear programming problem by using l₁ and l_∞ norm. To efficiently solve this LP, we propose the use of primal-dual infeasible-interior-point method with a warm start approach for closely related subsequent problem. With a SISO example and a MIMO example, we investigated the computation efficiency and fault detection performance of the data-based detector

Keywords

computational complexity; constraint theory; duality (mathematics); fault diagnosis; identification; linear programming; monitoring; LP; MIMO example; SISO example; computation efficiency; constrained optimization problem; data-based fault detection; fault detection performance; l_∞ norm; l₁ norm; linear programming; primal-dual infeasible-interior-point method; primal-dual interior point method; process monitoring; warm start; Analytical models; Chemical engineering; Equations; Fault detection; Integrated circuit modeling; Large-scale systems; Linear programming; Monitoring; Q measurement; Redundancy;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 1997. Proceedings of the 1997

Conference_Location

Albuquerque, NM

ISSN

0743-1619

Print_ISBN

0-7803-3832-4

Type

conf

DOI

10.1109/ACC.1997.611999

Filename

611999