Operator's model for control and optimization of industrial processes

S. Kim, W. Mahmood, G. Vachtsevanos, T. Samad

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

1 Scopus citations

Abstract

An operator's model is developed based on a polynomial fuzzy neural network architecture for control and optimization of industrial processes. Industrial processes possess complex dynamics which are accentuated under abnormal operating conditions. The operator plays a vital role in bringing the plant states back to a normal mode. In a typical industrial enterprise, knowledge of a specific process lies at three levels; skilled operator, process engineer, and design engineer. The model presented captures the operator's and engineer's corrective actions which are based on their experience and their knowledge of the system's behavioral patterns. The model is tested on a pH neutralization process and simulation results are presented.

Original languageEnglish (US)
Title of host publicationIEEE Conference on Control Applications - Proceedings
Editors Anon
PublisherIEEE
Pages95-100
Number of pages6
StatePublished - Dec 1 1996
EventProceedings of the 1996 IEEE International Conference on Control Applications - Dearborn, MI, USA
Duration: Sep 15 1996Sep 18 1996

Other

OtherProceedings of the 1996 IEEE International Conference on Control Applications
CityDearborn, MI, USA
Period9/15/969/18/96

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