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Please use this identifier to cite or link to this item: https://doi.org/10.1109/CCA.2007.4389317
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dc.titleAdaptive neural network control for marine shafting system using dynamic surface control
dc.contributor.authorTao, P.Y.
dc.contributor.authorGe, S.S.
dc.contributor.authorLee, T.H.
dc.date.accessioned2014-06-19T02:57:55Z
dc.date.available2014-06-19T02:57:55Z
dc.date.issued2007
dc.identifier.citationTao, P.Y.,Ge, S.S.,Lee, T.H. (2007). Adaptive neural network control for marine shafting system using dynamic surface control. Proceedings of the IEEE International Conference on Control Applications : 717-722. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/CCA.2007.4389317" target="_blank">https://doi.org/10.1109/CCA.2007.4389317</a>
dc.identifier.isbn1424404436
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/69197
dc.description.abstractIn this paper, we consider the problem of tracking a desired propeller shaft speed while simultaneously minimizing torsional vibrations within the shafting system, in the presence of parametric/functional uncertainties. Neural networks are utilized to compensate for the functional uncertainties in the system model. Under the proposed control, semiglobal uniform boundedness of the closed loop signals is guaranteed, and the number and size of neural networks required are significantly reduced. © 2007 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/CCA.2007.4389317
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/CCA.2007.4389317
dc.description.sourcetitleProceedings of the IEEE International Conference on Control Applications
dc.description.page717-722
dc.identifier.isiutNOT_IN_WOS
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