Publication: Identification and control of ITU Triga Mark-II Nuclear Research Reactor using neural networks and fuzzy logic
| dc.contributor.authors | Coban, R; Can, B | |
| dc.contributor.editor | Zhang, S | |
| dc.contributor.editor | Jarvis, R | |
| dc.date.accessioned | 2022-03-12T15:59:21Z | |
| dc.date.accessioned | 2026-01-11T17:13:01Z | |
| dc.date.available | 2022-03-12T15:59:21Z | |
| dc.date.issued | 2005 | |
| dc.description.abstract | In this paper, an artificial neural networks identifier and a fuzzy logic controller for ITU Triga Mark-II Nuclear Research Reactor is presented. Three parted control function is used as a reference trajectory that the fuzzy logic controller tracks. The nonlinear behavior of the reactor is identified by using generalized neural networks. The validity of the proposed identification model is tested by comparing these results with the ones obtained by YAVCAN code. The effectiveness of the controller is demonstrated on the neural network model. | |
| dc.identifier.doi | doiWOS:000235836100140 | |
| dc.identifier.isbn | 3-540-30462-2 | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.uri | https://hdl.handle.net/11424/224377 | |
| dc.identifier.wos | WOS:000235836100140 | |
| dc.language.iso | eng | |
| dc.publisher | SPRINGER-VERLAG BERLIN | |
| dc.relation.ispartof | AI 2005: ADVANCES IN ARTIFICIAL INTELLIGENCE | |
| dc.relation.ispartofseries | LECTURE NOTES IN ARTIFICIAL INTELLIGENCE | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.title | Identification and control of ITU Triga Mark-II Nuclear Research Reactor using neural networks and fuzzy logic | |
| dc.type | conferenceObject | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 1062 | |
| oaire.citation.startPage | 1057 | |
| oaire.citation.title | AI 2005: ADVANCES IN ARTIFICIAL INTELLIGENCE | |
| oaire.citation.volume | 3809 |