Please use this identifier to cite or link to this item: https://doi.org/10.1109/72.557689
DC FieldValue
dc.titleArtificial neural networks controlled fast valving in a power generation plant
dc.contributor.authorHan, Y.
dc.contributor.authorXiu, L.
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
dc.identifier.citationHan, Y., Xiu, L., Wang, Z., Chen, Q., Tan, S. (1997). Artificial neural networks controlled fast valving in a power generation plant. IEEE Transactions on Neural Networks 8 (2) : 373-389. ScholarBank@NUS Repository. https://doi.org/10.1109/72.557689
dc.identifier.issn10459227
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/61864
dc.description.abstractThis paper presents an artificial neural-network-based controller to realize the fast valving in a power generation plant. The backpropagation algorithm is used to train the feedforward neural networks controller. The hardware implementation and the test results of the controller on a physical pilot-scale power plant setup are described in detail. Compared with the conventional fast valving methods applied to the same system, test results both with the computer simulation and on a physical pilot-scale power plant setup demonstrate that the artificial neural-network controller has satisfactory generalization capability, reliability, and accuracy to be feasible for this critical control operation. © 1997 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/72.557689
dc.sourceScopus
dc.subjectArtificial neural networks
dc.subjectBackpropagation algorithm
dc.subjectFast valving
dc.subjectHardware implementation
dc.subjectPilot-scale power plant setup
dc.subjectPower generation plant
dc.subjectPower system stability
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.doi10.1109/72.557689
dc.description.sourcetitleIEEE Transactions on Neural Networks
dc.description.volume8
dc.description.issue2
dc.description.page373-389
dc.description.codenITNNE
dc.identifier.isiutA1997WM03800017
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