Show simple item record

dc.contributor.authorMadkour, A.A.M.*
dc.contributor.authorHossain, M. Alamgir*
dc.contributor.authorDahal, Keshav P.*
dc.contributor.authorYu, H.*
dc.date.accessioned2009-03-11T12:49:18Z
dc.date.available2009-03-11T12:49:18Z
dc.date.issued2004
dc.identifier.citationMadkour, A.A.M., Hossain, M.A., Dahal, K.P. and Yu, H. (2004) Realtime system identification using intelligent algorithms. In: Proceedings of the IEEE SMC UK-RI 3rd Chapter Conference on Intelligent Cybernetic Systems, (ICS¿04) September 7-8, 2004, Londonderry, U.K. pp 236-241.en
dc.identifier.urihttp://hdl.handle.net/10454/2471
dc.description.abstractThis research presents an investigation into the development of real time system identification using intelligent algorithms. A simulation platform of a flexible beam vibration using finite difference (FD) method is used to demonstrate the real time capabilities of the identification algorithms. A number of approaches and algorithms for on line system identifications are explored and evaluated to demonstrate the merits of the algorithms for real time implementation. These approaches include identification using (a) traditional recursive least square (RLS) filter, (b) Genetic Algorithms (GAs) and (c) adaptive Neuro_Fuzzy (ANFIS) model. The above algorithms are used to estimate a linear discrete second order model for the flexible beam vibration. The model is implemented, tested and validated to evaluate and demonstrate the merits of the algorithms for real time system identification. Finally, a comparative performance of error convergence and real time computational complexity of the algorithms is presented and discussed through a set of experiments.en
dc.language.isoenen
dc.publisherIEEEen
dc.relation.isreferencedbyhttp://ieeesmc-ukri.wikidot.com/ics2004en
dc.rightsCopyright © [2004] IEEE. Reprinted from Proceedings of the IEEE SMC UK-RI Chapter Conference on Intelligent Cybernetic Systems,September 7-8, 2004, Londonderry, U.K This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bradford's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubspermissions@ ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.en
dc.subjectSystem identificationen
dc.subjectAdaptive controlen
dc.subjectIntelligent identificationen
dc.subjectRecursive least squares algorithmen
dc.subjectGenetic algorithmsen
dc.subjectANFISen
dc.titleReal-time system identification using intelligent algorithmsen
dc.status.refereedYesen
dc.typeConference paperen
dc.type.versionpublished version paperen
refterms.dateFOA2018-07-18T13:34:06Z


Item file(s)

Thumbnail
Name:
2004-IEEE_SMC_ICS04-UK-RI-Real ...
Size:
266.4Kb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record