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 language | English |
|---|---|
| Title of host publication | 7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering - Congress Manuscripts |
| Pages | 55 |
| Number of pages | 1 |
| Publication status | Published - 2005 |
| Event | 7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering - Glasgow, Scotland, United Kingdom Duration: Jul 10 2005 → Jul 14 2005 |
Other
| Other | 7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering |
|---|---|
| Country | United Kingdom |
| City | Glasgow, Scotland |
| Period | 7/10/05 → 7/14/05 |
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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)