20598305

Source:http://linkedlifedata.com/resource/pubmed/id/20598305

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0087130, umls-concept:C0456387, umls-concept:C1708517, umls-concept:C2587213
pubmed:issue	4
pubmed:dateCreated	2010-9-6
pubmed:abstractText	Based on the universal approximation property of the fuzzy-neural networks, an adaptive fuzzy-neural observer design algorithm is studied for a class of nonlinear SISO systems with both a completely unknown function and an unknown dead-zone input. The fuzzy-neural networks are used to approximate the unknown nonlinear function. Because it is assumed that the system states are unmeasured, an observer needs to be designed to estimate those unmeasured states. In the previous works with the observer design based on the universal approximator, when the dead-zone input appears it is ignored and the stability of the closed-loop system will be affected. In this paper, the proposed algorithm overcomes the affections of dead-zone input for the stability of the systems. Moreover, the dead-zone parameters are assumed to be unknown and will be adjusted adaptively as well as the sign function being introduced to compensate the dead-zone. With the aid of the Lyapunov analysis method, the stability of the closed-loop system is proven. A simulation example is provided to illustrate the feasibility of the control algorithm presented in this paper.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/0374750
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Oct
pubmed:issn	1879-2022
pubmed:author	pubmed-author:LiuYan-JunYJ, pubmed-author:ZhouNingN
pubmed:copyrightInfo	Copyright © 2010. Published by Elsevier Ltd.
pubmed:issnType	Electronic
pubmed:volume	49
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	462-9
pubmed:meshHeading	pubmed-meshheading:20598305-Algorithms, pubmed-meshheading:20598305-Computer Simulation, pubmed-meshheading:20598305-Fuzzy Logic, pubmed-meshheading:20598305-Neural Networks (Computer), pubmed-meshheading:20598305-Nonlinear Dynamics
pubmed:year	2010
pubmed:articleTitle	Observer-based adaptive fuzzy-neural control for a class of uncertain nonlinear systems with unknown dead-zone input.
pubmed:affiliation	School of Sciences, Liaoning University of Technology, Jinzhou, Liaoning, 121001, PR China. liuyanjun@live.com
pubmed:publicationType	Journal Article, Research Support, Non-U.S. Gov't