A bio-inspired robust controller for a refinery plant process

Calvo Rolle, José L.; Corchado Rodríguez, Emilio Santiago

Título

dc.contributor.author	Calvo Rolle, José L.
dc.contributor.author	Corchado Rodríguez, Emilio Santiago
dc.date.accessioned	2017-09-05T11:01:47Z
dc.date.available	2017-09-05T11:01:47Z
dc.date.issued	2011
dc.identifier.citation	Logic Journal of IGPL. Volumen 20 (3), pp. 598-616. Oxford University Press (OUP).
dc.identifier.issn	1367-0751(Print)/ 1368-9894(Online)
dc.identifier.uri	http://hdl.handle.net/10366/134390
dc.description.abstract	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.
dc.format.mimetype	application/pdf
dc.language.iso	en
dc.publisher	Oxford University Press (OUP)
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.uri	https://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subject	Computer Science
dc.title	A bio-inspired robust controller for a refinery plant process
dc.type	info:eu-repo/semantics/article
dc.rights.accessRights	info:eu-repo/semantics/openAccess