Control of the speed and exhaust gas temperature in gas turbine using adaptive neuro-fuzzy inference system
Joint Authors
Hadroug, Nadji
Hafaifa, Ahmad
Kuzu, Abd Allah
Guimana, Mulud
Chaibit, Ahmad
Source
Journal of Automation and Systems Engineering
Issue
Vol. 10, Issue 3 (30 Sep. 2016), pp.158-167, 10 p.
Publisher
Publication Date
2016-09-30
Country of Publication
Algeria
No. of Pages
10
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
This work proposes the application of the hybrid approach using Adaptive Neuro-Fuzzy Inference System (ANFIS) to control the speed and exhaust gas temperature of a gas turbine.
Create into various parts of the model of the examined gas turbine and given a comprehensive procedure to derive the parameters of the investigated gas turbine using the parameters of Rowen’s model for dynamic studies, the parameters are estimated by use of available operational and performance data.
This paper develops the studied single shaft heavy duty gas turbine model L7001B class 160-MW simple cycle for deriving the parameters of the model.
The obtained results using the Adaptive Neuro- Fuzzy Inference System are validates by several robust tests
American Psychological Association (APA)
Hadroug, Nadji& Hafaifa, Ahmad& Kuzu, Abd Allah& Guimana, Mulud& Chaibit, Ahmad. 2016. Control of the speed and exhaust gas temperature in gas turbine using adaptive neuro-fuzzy inference system. Journal of Automation and Systems Engineering،Vol. 10, no. 3, pp.158-167.
https://search.emarefa.net/detail/BIM-754758
Modern Language Association (MLA)
Hadroug, Nadji…[et al.]. Control of the speed and exhaust gas temperature in gas turbine using adaptive neuro-fuzzy inference system. Journal of Automation and Systems Engineering Vol. 10, no. 3 (2016), pp.158-167.
https://search.emarefa.net/detail/BIM-754758
American Medical Association (AMA)
Hadroug, Nadji& Hafaifa, Ahmad& Kuzu, Abd Allah& Guimana, Mulud& Chaibit, Ahmad. Control of the speed and exhaust gas temperature in gas turbine using adaptive neuro-fuzzy inference system. Journal of Automation and Systems Engineering. 2016. Vol. 10, no. 3, pp.158-167.
https://search.emarefa.net/detail/BIM-754758
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 166-167
Record ID
BIM-754758