2024-03-29T13:08:54Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1348732024-02-14T09:20:25Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134811
A Novel Hybrid Intelligent Classifier to Obtain the Controller Tuning Parameters for Temperature Control
Calvo Rolle, José L.
Corchado Rodríguez, Emilio Santiago
Hernández Ramos, Pedro
Román Gallego, Jesús Ángel
Quintián Pardo, Héctor
Ferreiro García, Ramón
Computer Science
This study presents a novel hybrid classifier method to obtain the best parameters of a PID controller for desired specifications. The study presents a hybrid system based on the organization of existing rules and classifier models that select the optimal expressions to improve specifications. The model achieved chooses the best controller parameters among different closed loop tuning methods. The classifiers are based on ANN and SVM. The proposal was tested on the temperature control of a laboratory stove.
2017-09-06
2017-09-06
2012
info:eu-repo/semantics/article
Hybrid Artificial Intelligent Systems Lecture Notes in Computer Science. 7th International Conference, HAIS 2012, Salamanca, Spain, March 28-30th, 2012. Proceedings, Part I. Lecture Notes in Computer Science. Volumen 7208, pp. 677-689.
978-3-642-28941-5 (Print) / 978-3-642-28942-2 (Online)
0302-9743(Print)/ 1611-3349(Online)
http://hdl.handle.net/10366/134873
en
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivs 3.0 Unported
Springer Science + Business Media