Knowledge-based framework for controller structure selection in intelligent process control

Daniel Rivera, Abhijit Desai, Terrence Beaumariage, Chell Roberts

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Intelligent control principles are used to address the issue of combinatorial complexity in controller structure selection for plantwide control, i.e., the variables selection and pairing problem. A knowledge-based framework combining symbolic representation of heuristics and designer expertise, simple analytical 'ranking' criteria, and more elaborate computational routines for selection and pairing is described in this paper. The use of an object-oriented structure leads to a system that is flexible, extensible, and multipurpose, which are features necessary if industrial engineering organizations are to adopt this tool on a routine basis.

Original languageEnglish (US)
Title of host publicationAmerican Control Conference
Editors Anon
PublisherPubl by IEEE
Pages1890-1894
Number of pages5
ISBN (Print)0780308611
StatePublished - Dec 1 1993
EventProceedings of the 1993 American Control Conference Part 3 (of 3) - San Francisco, CA, USA
Duration: Jun 2 1993Jun 4 1993

Publication series

NameAmerican Control Conference

Other

OtherProceedings of the 1993 American Control Conference Part 3 (of 3)
CitySan Francisco, CA, USA
Period6/2/936/4/93

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Rivera, D., Desai, A., Beaumariage, T., & Roberts, C. (1993). Knowledge-based framework for controller structure selection in intelligent process control. In Anon (Ed.), American Control Conference (pp. 1890-1894). (American Control Conference). Publ by IEEE.