Please use this identifier to cite or link to this item: http://148.72.244.84/xmlui/handle/xmlui/4327
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dc.contributor.authorIntisar N. Al-Obaidi-
dc.contributor.authorAbbas H. Issa-
dc.date.accessioned2023-10-17T16:08:26Z-
dc.date.available2023-10-17T16:08:26Z-
dc.date.issued2016-
dc.identifier.citationUniversity of Diyala – College of Engineeringen_US
dc.identifier.issn1999-8716-
dc.identifier.urihttps://djes.info/index.php/djes-
dc.identifier.urihttp://148.72.244.84:8080/xmlui/handle/xmlui/4327-
dc.description.abstractDifferent types of controllers are designed in this research to control the temperature of medical oven. These controllers represented by the conventional PID, the intelligent Neural Network (NN), Fuzzy-Logic controller (FLC) and the hybrid Adaptive-Neuro-Fuzzy-Inference-System (ANFIS) controller. The controllers designed using MATLAB R2012a version 7.14 both m-file and Simulink. Two laboratory ovens (lab ovens) with different mathematical models are used. A comparison between the designed controllers has been made, first with step response with the first oven and second with different set points of four medical applications for the second practical lab oven, the ANFIS superiority over the others has been proven which highlighted the hybridization power and efficiency and its suitability for controlling the temperature of medical oven.en_US
dc.language.isoenen_US
dc.subjectModelingen_US
dc.subjectMedical Ovenen_US
dc.subjectPIDen_US
dc.subjectFLCen_US
dc.subjectNNen_US
dc.subjectANFISen_US
dc.titleMedical Oven Temperature Control Based on Soft Computing Techniquesen_US
dc.typeArticleen_US
Appears in Collections:مجلة ديالى للعلوم الهندسية / Diyala Journal of Engineering Sciences (DJES)

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