dc.creator | Morles, E.C | |
dc.date.accessioned | 2018-01-11T16:47:17Z | |
dc.date.accessioned | 2022-10-21T00:05:36Z | |
dc.date.available | 2018-01-11T16:47:17Z | |
dc.date.available | 2022-10-21T00:05:36Z | |
dc.date.created | 2018-01-11T16:47:17Z | |
dc.date.issued | 2015-08-15 | |
dc.identifier | 9781467376822 | |
dc.identifier | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966601941&doi=10.1109%2fFSKD.2015.7382001&partnerID=40&md5=9cd52a3e631514e7e4d368a1b0a23be9 | |
dc.identifier | http://dspace.ucuenca.edu.ec/handle/123456789/29060 | |
dc.identifier | 10.1109/FSKD.2015.7382001 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/4621861 | |
dc.description.abstract | This paper presents an identification approach based on invertible singleton fuzzy models in order to implement a control system for a progressive cavity pump-based petroleum production system, by using the inverse model control scheme. The identification proposal uses input-output process variables measurements and an off-line genetic algorithm, which is designed for guarantying the analytical calculation of the inverse model. Regarding the application of the genetic algorithm, three selection methods are evaluated: tournament selection, roulette wheel selection and linear rank selection. Once the fuzzy singleton model is identified, the controller design is a straightforward procedure. Computer simulations show the potential application of this kind of model in real industrial control processes. | |
dc.language | en_US | |
dc.publisher | INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC. | |
dc.source | 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015 | |
dc.subject | Genetic Algorithm | |
dc.subject | Inversion Of Fuzzy Models | |
dc.subject | Progressive Cavity Pumps | |
dc.subject | Singleton Fuzzy Models | |
dc.title | Invertible singleton fuzzy models: Application to petroleum production control systems | |
dc.type | Article | |