One-Step-Ahead Predictive Control for Hydroturbine Governor

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dc.contributor.authorXiao, Zhihuai
dc.contributor.authorMeng, Suili
dc.contributor.authorLu, Na
dc.contributor.authorMalik, O. P.
dc.date.accessioned2018-09-27T11:26:50Z
dc.date.available2018-09-27T11:26:50Z
dc.date.issued2015-09-16
dc.date.updated2018-09-27T11:26:50Z
dc.description.abstractThe hydroturbine generator regulating system can be considered as one system synthetically integrating water, machine, and electricity. It is a complex and nonlinear system, and its configuration and parameters are time-dependent. A one-step-ahead predictive control based on on-line trained neural networks (NNs) for hydroturbine governor with variation in gate position is described in this paper. The proposed control algorithm consists of a one-step-ahead neuropredictor that tracks the dynamic characteristics of the plant and predicts its output and a neurocontroller to generate the optimal control signal. The weights of two NNs, initially trained off-line, are updated on-line according to the scalar error. The proposed controller can thus track operating conditions in real-time and produce the optimal control signal over the wide operating range. Only the inputs and outputs of the generator are measured and there is no need to determine the other states of the generator. Simulations have been performed with varying operating conditions and different disturbances to compare the performance of the proposed controller with that of a conventional PID controller and validate the feasibility of the proposed approach.
dc.description.versionPeer Reviewed
dc.identifier.citationZhihuai Xiao, Suili Meng, Na Lu, and O. P. Malik, “One-Step-Ahead Predictive Control for Hydroturbine Governor,” Mathematical Problems in Engineering, vol. 2015, Article ID 382954, 10 pages, 2015. doi:10.1155/2015/382954
dc.identifier.doihttps://doi.org/10.1155/2015/382954
dc.identifier.urihttp://hdl.handle.net/1880/108152
dc.language.rfc3066en
dc.rights.holderCopyright © 2015 Zhihuai Xiao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.titleOne-Step-Ahead Predictive Control for Hydroturbine Governor
dc.typeJournal Article
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