<efrbr:recordSet xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:efrbr="http://vfrbr.info/efrbr/1.1" xmlns:efrbr-work="http://vfrbr.info/efrbr/1.1/work" xmlns:efrbr-expression="http://vfrbr.info/efrbr/1.1/expression" xmlns:efrbr-manifestation="http://vfrbr.info/efrbr/1.1/manifestation" xmlns:efrbr-person="http://vfrbr.info/efrbr/1.1/person" xmlns:efrbr-corporateBody="http://vfrbr.info/efrbr/1.1/corporateBody" xmlns:efrbr-concept="http://vfrbr.info/efrbr/1.1/concept" xmlns:efrbr-structure="http://vfrbr.info/efrbr/1.1/structure" xmlns:efrbr-responsible="http://vfrbr.info/efrbr/1.1/responsible" xmlns:efrbr-subject="http://vfrbr.info/efrbr/1.1/subject" xmlns:efrbr-other="http://vfrbr.info/efrbr/1.1/other" xsi:schemaLocation="http://vfrbr.info/efrbr/1.1 http://vfrbr.info/schemas/1.1/efrbr.xsd"><efrbr:entities><efrbr-work:work identifier="http://purl.tuc.gr/dl/dias/E299E319-3BB0-42AF-9D7E-E3A5E4BD7446"><efrbr-work:titleOfTheWork>Adaptive backstepping neural network control for mechanical pumps</efrbr-work:titleOfTheWork></efrbr-work:work><efrbr-expression:expression identifier="http://purl.tuc.gr/dl/dias/E299E319-3BB0-42AF-9D7E-E3A5E4BD7446"><efrbr-expression:titleOfTheExpression>Adaptive backstepping neural network control for mechanical pumps</efrbr-expression:titleOfTheExpression><efrbr-expression:formOfExpression vocabulary="DIAS:TYPES">
            Peer-Reviewed Journal Publication
            Δημοσίευση σε Περιοδικό με Κριτές
         </efrbr-expression:formOfExpression><efrbr-expression:dateOfExpression type="issued">2020-11-19</efrbr-expression:dateOfExpression><efrbr-expression:dateOfExpression type="published">2012</efrbr-expression:dateOfExpression><efrbr-expression:languageOfExpression vocabulary="iso639-1">en</efrbr-expression:languageOfExpression><efrbr-expression:summarizationOfContent> In this paper, an Adaptive Backstepping Neural Network control approach is
used for a class of affine nonlinear systems which describe the pump model in the strict feedback form. The close loop signals are semi globally uniformly ultimately bounded and the output of the system is proven to follow a desired trajectory. Simulation results are presented to show the effectiveness of the approach proposed in order to control the pump output.</efrbr-expression:summarizationOfContent><efrbr-expression:useRestrictionsOnTheExpression type="creative-commons">http://creativecommons.org/licenses/by/4.0/</efrbr-expression:useRestrictionsOnTheExpression><efrbr-expression:note type="journal name">Chaotic Modeling and Simulation</efrbr-expression:note><efrbr-expression:note type="journal volume">1</efrbr-expression:note><efrbr-expression:note type="page range">109-122</efrbr-expression:note></efrbr-expression:expression><efrbr-person:person identifier="http://viaf.org/viaf/296926980"><efrbr-person:nameOfPerson vocabulary="VIAF">
            Vamvoudakis, Kyriakos G., 1983-
         </efrbr-person:nameOfPerson></efrbr-person:person><efrbr-person:person identifier="http://users.isc.tuc.gr/~manolis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Christodoulou Manolis
            Χριστοδουλου Μανωλης
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            CMSIM
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            Adaptive backstepping neural network
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