2024-03-29T04:43:28Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1343902024-03-13T09:52:58Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134243
A bio-inspired robust controller for a refinery plant process
Calvo Rolle, José L.
Corchado RodrÃguez, Emilio Santiago
Computer Science
This research presents a novel bio-inspired knowledge method, based on gain scheduling, for the calculation of Proportional-Integral-Derivative controller parameters that will prevent system instability. The aim is to prevent a transition to control system instability due to undesirable controller parameters that may be introduced manually by an operator. Each significant operation point in the system is identified first. Then, a solid stability structure is calculated, using transfer functions, in order to program a bio-inspired model by using an artificial neural network. The novel method is empirically verified under working conditions in a real refinery plant process.
2017-09-05
2017-09-05
2011
info:eu-repo/semantics/article
Logic Journal of IGPL. Volumen 20 (3), pp. 598-616. Oxford University Press (OUP).
1367-0751(Print)/ 1368-9894(Online)
http://hdl.handle.net/10366/134390
en
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivs 3.0 Unported
Oxford University Press (OUP)