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

    Fingerprint

    Fluid catalytic cracking
    Model predictive control
    Neural networks
    Disturbance rejection
    Chemical engineering

    All Science Journal Classification (ASJC) codes

    • Energy(all)

    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)
    Cristea, V. M. ; Toma, L. ; Agachi, S. P. / Neural networks used for model predictive control of the fluid catalytic cracking unit. 7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering - Congress Manuscripts. 2005. pp. 55
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    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).",
    author = "Cristea, {V. M.} and L. Toma and Agachi, {S. P.}",
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    Cristea, VM, Toma, L & Agachi, SP 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, 7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering, Glasgow, Scotland, United Kingdom, 7/10/05.

    Neural networks used for model predictive control of the fluid catalytic cracking unit. / Cristea, V. M.; Toma, L.; Agachi, S. P.

    7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering - Congress Manuscripts. 2005. p. 55.

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

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    AB - 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).

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    Cristea VM, Toma L, Agachi SP. 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. 2005. p. 55