Fault diagnosis of an industrial CGO coker model predictive control system

Author

Huang, B. ; Zhao, X. ; Tamayo, E.C. ; Hanafi, A.

Author_Institution

Dept. of Chem. & Mater. Eng., Alberta Univ., Edmonton, Alta., Canada

Volume

2

fYear

1999

fDate

9-12 May 1999

Firstpage

960

Abstract

We report a successful fault diagnosis and trouble shooting process of an industrial model predictive control system. The approach is completely data driven. Routine closed-loop operating data is the only information required for applying such a diagnosis. The source of the problem has been attributed to inappropriate selection of the disturbance variables for the MPC controller. The problem is not unusual in industrial model predictive control systems. It is therefore recommended to carry out such analysis to other industrial MPC control systems as well.

Keywords

control system analysis computing; fault diagnosis; multivariable control systems; oil refining; predictive control; combined gas oil coker; data driven approach; disturbance variables; industrial CGO coker; model predictive control system; trouble shooting process; Constraint optimization; Control system synthesis; Control systems; Electrical equipment industry; Fault diagnosis; Fuel processing industries; Industrial control; Predictive control; Predictive models; Voltage control;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 1999 IEEE Canadian Conference on

Conference_Location

Edmonton, Alberta, Canada

ISSN

0840-7789

Print_ISBN

0-7803-5579-2

Type

conf

DOI

10.1109/CCECE.1999.808163

Filename

808163