Fuzzy Neural Network-based Model Reference Adaptive Inverse Control for Induction Machines

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dc.contributor.author Shao, Zhongkai en_US
dc.contributor.author Zhan, Yuedong en_US
dc.contributor.author Guo, Youguang en_US
dc.contributor.editor Jin, J. en_US
dc.date.accessioned 2010-05-28T09:58:43Z
dc.date.available 2010-05-28T09:58:43Z
dc.date.issued 2009 en_US
dc.identifier 2009000599 en_US
dc.identifier.citation Shao Zhongkai, Zhan Yuedong, and Guo Youguang 2009, 'Fuzzy Neural Network-based Model Reference Adaptive Inverse Control for Induction Machines', IEEE, USA, pp. 56-59. en_US
dc.identifier.issn 978-1-4244-3687-3 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/10698
dc.description.abstract In this paper, because the induction machines are described as the plants of highly nonlinear and parameters timevarying, in order to obtain a very well control performances that a conventional model reference adaptive inverse control (MRAIC) can not be gotten, a fuzzy neural network-based model reference adaptive inverse control strategy for induction motors is presented based on the rotor field oriented motion model of induction machines. The fuzzy neural network control (FNNC) is incorporated into the model reference adaptive control (MRAC), a fuzzy basis function network controller (FBNC) and a fuzzy neural network identifier (FNNI) for asynchronous motors adjustable speed system are designed. The proposed controller for asynchronous machines resolves the shortage of MRAC, and employs the advantages of FNNC and MRAC. Simulation results show that the proposed control strategy is of the feasibility, correctness and effectiveness. en_US
dc.language English en_US
dc.publisher IEEE en_US
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon NA en_US
dc.title Fuzzy Neural Network-based Model Reference Adaptive Inverse Control for Induction Machines en_US
dc.parent Proceedings of IEEE International Conference on Applied Superconductivity and Electromagnetic Devices en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation USA en_US
dc.identifier.startpage 56 en_US
dc.identifier.endpage 59 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 040401 en_US
dc.personcode 0000054613 en_US
dc.personcode 0000025999 en_US
dc.personcode 990817 en_US
dc.percentage 100 en_US
dc.classification.name Electrical and Electromagnetic Methods in Geophysics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom IEEE International Conference on Applied Superconductivity and Electromagnetic Devices en_US
dc.date.activity 20090925 en_US
dc.location.activity Chengdu, China en_US
dc.description.keywords induction machine; mochine dynamic model; fuzzy neural network control (FNNC); model reference adaptive control (MRAC) en_US
dc.staffid 990817 en_US


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