Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/61865
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dc.titleArtificial-neural-network-based fast valving control in a power-generation system
dc.contributor.authorHan, Y.
dc.contributor.authorWang, Z.
dc.contributor.authorChen, Q.
dc.contributor.authorTan, S.
dc.date.accessioned2014-06-17T06:44:51Z
dc.date.available2014-06-17T06:44:51Z
dc.date.issued1997-04
dc.identifier.citationHan, Y.,Wang, Z.,Chen, Q.,Tan, S. (1997-04). Artificial-neural-network-based fast valving control in a power-generation system. Engineering Applications of Artificial Intelligence 10 (2) : 139-155. ScholarBank@NUS Repository.
dc.identifier.issn09521976
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/61865
dc.description.abstractThis paper presents an artificial-neural-network-based controller to realize fast valving in a power-generation plant. A backpropagation algorithm is used to train the feedforward neural-network controller. The hardware implementation and the test results of the controller on a physical pilot-scale power system set-up are described in detail. Compared with some conventional fast valving methods applied to the same system, test results (both in a computer simulation and on a physical pilot-scale power system set-up) show that the neural-network controller has quite satisfactory generalisation capability, feasibility and reliability, as well as accuracy. © 1997 Elsevier Science Ltd. All rights reserved.
dc.sourceScopus
dc.subjectArtificial neural networks
dc.subjectBackpropagation algorithm
dc.subjectFast valving
dc.subjectHardware implementation
dc.subjectPilot-scale power systems set-ups
dc.subjectPower-generation systems
dc.subjectTransient stability
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.sourcetitleEngineering Applications of Artificial Intelligence
dc.description.volume10
dc.description.issue2
dc.description.page139-155
dc.description.codenEAAIE
dc.identifier.isiutNOT_IN_WOS
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