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Control of A Cantilever Pipe Conveying Fluid using Neural Network

dc.contributor.authorDemir, Mehmet Hakan
dc.contributor.authorYesildirek, Aydin
dc.contributor.authorYigit, Faruk
dc.contributor.institutionauthorYEŞİLDİREK, Aydın
dc.date.accessioned2026-06-27T13:36:40Z
dc.date.issued2015
dc.description.abstractThe purpose of this paper is to investigate the dynamic behavior of a fluid conveying pipe and to propose suitable control strategies in order to eliminate or suppress its vibration. The system under consideration consists of a uniform, straight, vertical cantilever pipe which conveys incompressible fluid. Governing equation of motion for free transverse vibration is derived by using Newtonian approach. This equation is discretized using the finite element method. The effects of the fluid flow speed on open loop response of the system are investigated. The results show unstable behavior when the flow velocity exceeds a critical value. Neural network based controller are applied to the system to suppress the pipe vibration and to improve the stability conditions. The results show that neural network based controller successfully suppresses the vibration when the critical flow velocity is exceeded. Moreover, it holds the system response in the stable region at higher flow velocities. NN based controller learns the variation of the system against unknown flow velocities in the system and adapts itself against unknown changes.en
dc.identifier.isbn978-1-4673-6601-4
dc.identifier.issn2473-4748
dc.identifier.urihttps://hdl.handle.net/20.500.14981/53708
dc.identifier.wos000380551800004
dc.language.isoeng
dc.publisherIEEE
dc.relation.conference6th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO)
dc.relation.ispartof2015 6TH INTERNATIONAL CONFERENCE ON MODELING, SIMULATION, AND APPLIED OPTIMIZATION (ICMSAO)
dc.subjectVIBRATION SUPPRESSION
dc.subjectEngineering
dc.titleControl of A Cantilever Pipe Conveying Fluid using Neural Network
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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