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dc.contributor.authorAl Mashhadany, Yousif-
dc.contributor.authorAl – Faiz, Mohammad. Z.-
dc.date.accessioned2022-10-20T21:03:01Z-
dc.date.available2022-10-20T21:03:01Z-
dc.date.issued2002-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/4197-
dc.description.abstractFor nonlinear systems, the method of directly adjusting the parameter of the controller using the adaptive control are not available. This is because the unknown nonlinear system lies between the controller and the output error. This paper explains the abilities of FRBP network to capture the nonlinearity and this will often the ability to overcome the problem of direct adaptive control in nonlinear system. Two neural networks are used as a controller for a pitch channel for BTT missile control system, the simulation results shown the ability of FRBP for capture the nonlinearity rather than fast BP.en_US
dc.language.isoenen_US
dc.publisher4th International Conference on Computational Aspects and Their Applications in Electrical Eng,(CATAEE) Jordan 2002en_US
dc.subjectNeural Networksen_US
dc.subjectFinite Recurrent Back Propagation FRBPen_US
dc.subjectdirect adaptive controlen_US
dc.titleDirect Neuro – Adaptive Controller Based on Finite Recurrent Back Propagation (FRBP) Networken_US
dc.typeArticleen_US
Appears in Collections:الهندسة الكهربائية

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