Adaptive Self-Tuning Neuro Wavelet Network Controllers

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dc.contributor.authorLekutai, Gaviphaten
dc.contributor.committeechairVanLandingham, Hugh F.en
dc.contributor.committeememberMoose, Richard L.en
dc.contributor.committeememberHannsgen, Kenneth B.en
dc.contributor.committeememberBesieris, Ioannis M.en
dc.contributor.committeememberReed, Jeffrey H.en
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2014-03-14T20:22:12Zen
dc.date.adate1997-03-31en
dc.date.available2014-03-14T20:22:12Zen
dc.date.issued1997-03-31en
dc.date.rdate1997-03-31en
dc.date.sdate1998-07-18en
dc.description.abstractSingle layer feed forward neural networks with hidden nodes of adaptive wavelet functions (wavenets) have been successfully demonstrated to have potential in many applications. Yet applications in the process control area have not been investigated. In this paper an application to a self-tuning design method for an unknown nonlinear system is presented. Different types of frame wavelet functions are integrated for their simplicity, availability, and capability of constructing adaptive controllers. Infinite impulse response (IIR) recurrent structures are combined in cascade to the network to provide a double local structure resulting in improved speed of learning. In particular, neuro-based controllers assume a certain model structure to approximate the system dynamics of the "unknown" plant and generate the control signal. The capability of neuro-controllers to self-tuning of an unknown nonlinear plants is then illustrated through design examples. Simulation results demonstrate that the self-tuning design methods are directly applicable for a large class of nonlinear control systems.en
dc.description.degreePh. D.en
dc.identifier.otheretd-554502439741131en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-554502439741131/en
dc.identifier.urihttp://hdl.handle.net/10919/30603en
dc.publisherVirginia Techen
dc.relation.haspartETD.PDFen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectnoneen
dc.titleAdaptive Self-Tuning Neuro Wavelet Network Controllersen
dc.typeDissertationen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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