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dc.contributor.authorZeng, H.
dc.contributor.authorTeo, Kok Lay
dc.contributor.authorHe, Y.
dc.contributor.authorWang, W.
dc.date.accessioned2019-02-19T04:16:58Z
dc.date.available2019-02-19T04:16:58Z
dc.date.created2019-02-19T03:58:21Z
dc.date.issued2019
dc.identifier.citationZeng, H. and Teo, K.L. and He, Y. and Wang, W. 2019. Sampled-data stabilization of chaotic systems based on a T-S fuzzy model. Information Sciences. 483: pp. 262-272.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/74444
dc.identifier.doi10.1016/j.ins.2019.01.046
dc.description.abstract

© 2019 Elsevier Inc. This paper investigates the problem of stability and stabilization of a class of chaotic system through the use of sampled-data control. By employing a Takagi–Sugeno (T-S) fuzzy model to describe the chaotic system and using a time-dependent Lyapunov function, an exponential stability condition is derived for the resulting closed-loop systems with input saturation constraint. Based on this condition, a fuzzy sampled-data controller is designed to stabilize the systems under consideration. The results obtained in this paper are based on the actual characteristic of sampling model. They depend explicitly on both the upper and lower bounds of sampling intervals. The chaotic Lorenz system is considered and solved by using the proposed approach so as to demonstrate the benefits and the superiority of the proposed approach over existing methods.

dc.publisherElsevier Inc
dc.titleSampled-data stabilization of chaotic systems based on a T-S fuzzy model
dc.typeJournal Article
dcterms.source.volume483
dcterms.source.startPage262
dcterms.source.endPage272
dcterms.source.issn0020-0255
dcterms.source.titleInformation Sciences
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Science (EECMS)
curtin.accessStatusFulltext not available


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