Robust adaptive control for greenhouse climate using neural networks

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dc.contributor.authorLuan, X.
dc.contributor.authorShi, P.
dc.contributor.authorLiu, F.
dc.date.issued2011
dc.description.abstract<jats:title>Abstract</jats:title><jats:p>This paper presents a general framework for robust adaptive neural network (NN)‐based feedback linearization controller design for greenhouse climate system. The controller is based on the well‐known feedback linearization, combined with radial basis functions NNs, which allows the feedback linearization technique to be used in an adaptive way. In addition, a robust sliding mode control is incorporated to deal with the bounded disturbances and the approximation errors of NNs. As a result, an inherently nonlinear robust adaptive control law is obtained, which not only provides fast and accurate tracking of varying set‐points, but also guarantees asymptotic tracking even if there are inherent approximation errors. Copyright © 2010 John Wiley &amp; Sons, Ltd.</jats:p>
dc.description.statementofresponsibilityXiaoli Luan, Peng Shi and Fei Liu
dc.identifier.citationInternational Journal of Robust and Nonlinear Control, 2011; 21(7):815-826
dc.identifier.doi10.1002/rnc.1630
dc.identifier.issn1049-8923
dc.identifier.issn1099-1239
dc.identifier.orcidShi, P. [0000-0001-6295-0405] [0000-0001-8218-586X] [0000-0002-0864-552X] [0000-0002-1358-2367] [0000-0002-5312-5435]
dc.identifier.urihttp://hdl.handle.net/2440/83527
dc.language.isoen
dc.publisherJohn Wiley & Sons Ltd
dc.rightsCopyright © 2010 John Wiley & Sons, Ltd.
dc.source.urihttps://doi.org/10.1002/rnc.1630
dc.subjectgreenhouse
dc.subjectclimate control
dc.subjectadaptive control
dc.subjectfeedback linearization
dc.subjectneural networks
dc.titleRobust adaptive control for greenhouse climate using neural networks
dc.typeJournal article
pubs.publication-statusPublished

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