Augmented model-based double iterative loop techniques for hierarchical control of complex industrial processes

M. Brdys, Normah Abdullah, P. D. Roberts

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Two novel hierarchical structures are presented which extend the applicability of previous model-based double iterative loop techniques using input-output information feedback to non-convex problems. The techniques incorporate integrated system optimization and parameter estimation, which utilize process measurements to achieve real process optimality in spite of model reality differences. The double iterative loop structures of the proposed algorithms use the real process measurements within the output loops while the inner loops involve model-based computations only. By this means the algorithms use available information from the real process efficiently and a significant reduction in set-point alterations to real subprocesses is achieved.

Original languageEnglish
Pages (from-to)549-570
Number of pages22
JournalInternational Journal of Control
Volume52
Issue number3
Publication statusPublished - Sep 1990

Fingerprint

Information use
Parameter estimation
Feedback

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Augmented model-based double iterative loop techniques for hierarchical control of complex industrial processes. / Brdys, M.; Abdullah, Normah; Roberts, P. D.

In: International Journal of Control, Vol. 52, No. 3, 09.1990, p. 549-570.

Research output: Contribution to journalArticle

@article{808e690ff36c42d1b2e438db6ec1e28a,
title = "Augmented model-based double iterative loop techniques for hierarchical control of complex industrial processes",
abstract = "Two novel hierarchical structures are presented which extend the applicability of previous model-based double iterative loop techniques using input-output information feedback to non-convex problems. The techniques incorporate integrated system optimization and parameter estimation, which utilize process measurements to achieve real process optimality in spite of model reality differences. The double iterative loop structures of the proposed algorithms use the real process measurements within the output loops while the inner loops involve model-based computations only. By this means the algorithms use available information from the real process efficiently and a significant reduction in set-point alterations to real subprocesses is achieved.",
author = "M. Brdys and Normah Abdullah and Roberts, {P. D.}",
year = "1990",
month = "9",
language = "English",
volume = "52",
pages = "549--570",
journal = "International Journal of Control",
issn = "0020-7179",
publisher = "Taylor and Francis Ltd.",
number = "3",

}

TY - JOUR

T1 - Augmented model-based double iterative loop techniques for hierarchical control of complex industrial processes

AU - Brdys, M.

AU - Abdullah, Normah

AU - Roberts, P. D.

PY - 1990/9

Y1 - 1990/9

N2 - Two novel hierarchical structures are presented which extend the applicability of previous model-based double iterative loop techniques using input-output information feedback to non-convex problems. The techniques incorporate integrated system optimization and parameter estimation, which utilize process measurements to achieve real process optimality in spite of model reality differences. The double iterative loop structures of the proposed algorithms use the real process measurements within the output loops while the inner loops involve model-based computations only. By this means the algorithms use available information from the real process efficiently and a significant reduction in set-point alterations to real subprocesses is achieved.

AB - Two novel hierarchical structures are presented which extend the applicability of previous model-based double iterative loop techniques using input-output information feedback to non-convex problems. The techniques incorporate integrated system optimization and parameter estimation, which utilize process measurements to achieve real process optimality in spite of model reality differences. The double iterative loop structures of the proposed algorithms use the real process measurements within the output loops while the inner loops involve model-based computations only. By this means the algorithms use available information from the real process efficiently and a significant reduction in set-point alterations to real subprocesses is achieved.

UR - http://www.scopus.com/inward/record.url?scp=0025486370&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0025486370&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0025486370

VL - 52

SP - 549

EP - 570

JO - International Journal of Control

JF - International Journal of Control

SN - 0020-7179

IS - 3

ER -