DocumentCode
1356423
Title
Algorithms for industrial model predictive control
Author
Sandoz, David J. ; Desforges, Matthew J. ; Lennox, Barry ; Goulding, Peter R.
Author_Institution
Sch. of Eng., Manchester Univ., UK
Volume
11
Issue
3
fYear
2000
fDate
6/1/2000 12:00:00 AM
Firstpage
125
Lastpage
134
Abstract
The article is concerned with control methods that have been embedded in an industrial model predictive control software package and that have been applied to a wide variety of industrial processes. Three methods are described and the various features are evaluated by considering a constrained multivariable simulation. One method has been in use since 1988 and is widely exploited in industry. The latest methods employ quadratic programming, which has become realistic to employ because of the advances in computing. The relative attributes are contrasted by assessing the ability of the controllers to recover effectively from the impact of a large unmeasured disturbance.
Keywords
process control; constrained multivariable simulation; control methods; industrial model predictive control algorithms; industrial process control; large unmeasured disturbance; quadratic programming; relative attributes; software package;
fLanguage
English
Journal_Title
Computing & Control Engineering Journal
Publisher
iet
ISSN
0956-3385
Type
jour
DOI
10.1049/cce:20000306
Filename
850787
Link To Document