Modeling and adaptive tracking for a class of stochastic Lagrangian control systems

dc.contributor.authorCui, M.
dc.contributor.authorWu, Z.
dc.contributor.authorXie, X.
dc.contributor.authorShi, P.
dc.date.issued2013
dc.description.abstractThis paper focuses on the problem of modeling and adaptive tracking for a class of stochastic Lagrangian control systems with unknown parameters. By reasonably introducing random noise, a method to construct stochastic Lagrangian control systems is given. Under some milder assumptions, an adaptive tracking controller is designed such that the mean square of the tracking error converges to an arbitrarily small neighborhood of zero by tuning design parameters. The reasonability of assumptions and the efficiency of the controller are demonstrated by a mechanics model in random vibration environment.
dc.description.statementofresponsibilityMing-Yue Cui, Zhao-Jing Wu, Xue-Jun Xie, Peng Shi
dc.identifier.citationAutomatica, 2013; 49(3):770-779
dc.identifier.doi10.1016/j.automatica.2012.11.013
dc.identifier.issn0005-1098
dc.identifier.issn1873-2836
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/2440/78309
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltd
dc.rightsCopyright © 2012 Elsevier Ltd. All rights reserved.
dc.source.urihttps://doi.org/10.1016/j.automatica.2012.11.013
dc.subjectStochastic Lagrangian control systems
dc.subjectAdaptive tracking
dc.subjectMechanics model
dc.titleModeling and adaptive tracking for a class of stochastic Lagrangian control systems
dc.typeJournal article
pubs.publication-statusPublished

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