Neural networks used for model predictive control of the fluid catalytic cracking unit

V. M. Cristea, L. Toma, S. P. Agachi

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

1 Citation (Scopus)

Abstract

A statistical model using neural networks (NN) has been developed for an industrial FCC unit (FCCU) of Universal Oil Products type. The emerged NN model was used to implement FCCU control using nonlinear model predictive control (NMPC) algorithm. The control performance of the NMPC based on NN model was studied in the presence of representative disturbances. Both control performance requirements, setpoint tracking, and disturbance rejection, were fulfilled showing short settling time, reduced overshoot, and zero offset. This is an abstract of a paper presented at the 7th World Congress of Chemical Engineering (Glasgow, Scotland 7/10-14/2005).

Original languageEnglish
Title of host publication7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering - Congress Manuscripts
Pages55
Number of pages1
Publication statusPublished - 2005
Event7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering - Glasgow, Scotland, United Kingdom
Duration: Jul 10 2005Jul 14 2005

Other

Other7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering
CountryUnited Kingdom
CityGlasgow, Scotland
Period7/10/057/14/05

All Science Journal Classification (ASJC) codes

  • Energy(all)

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  • Cite this

    Cristea, V. M., Toma, L., & Agachi, S. P. (2005). Neural networks used for model predictive control of the fluid catalytic cracking unit. In 7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering - Congress Manuscripts (pp. 55)