Control relevant system identification using orthonormal basis filters
Control relevant system identification deals with developing a dynamic model that can be used for design of a controller from experimental data. In this paper an iterative technique based on orthonormal basis filters is used to develop reduced complexity, control relevant models from input-output da...
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2007
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my.utp.eprints.5732017-01-19T08:27:15Z Control relevant system identification using orthonormal basis filters Tufa , L.D. Ramasamy , Marappagounder Shuhaimi , M. Patwardhan , S.C. TP Chemical technology Control relevant system identification deals with developing a dynamic model that can be used for design of a controller from experimental data. In this paper an iterative technique based on orthonormal basis filters is used to develop reduced complexity, control relevant models from input-output data that is corrupted with noise. It is also shown that a parsimonious general orthonormal basis filter (GOBF) model can be developed from a crude estimate of time constant with no prior knowledge of time delay. Unlike ARX, ARMAX and similar techniques the method presented does not require prior knowledge of the time delay. The identification technique is tested using simulated data and the result is found to be sufficiently accurate. ©2007 IEEE. 2007 Conference or Workshop Item NonPeerReviewed application/pdf http://eprints.utp.edu.my/573/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-57949098588&partnerID=40&md5=854e2d34fdc31225c62006a63600f2f2 Tufa , L.D. and Ramasamy , Marappagounder and Shuhaimi , M. and Patwardhan , S.C. (2007) Control relevant system identification using orthonormal basis filters. In: 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007 , 25 November 2007 through 28 November 2007 , Kuala Lumpur . http://eprints.utp.edu.my/573/ |
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TP Chemical technology Tufa , L.D. Ramasamy , Marappagounder Shuhaimi , M. Patwardhan , S.C. Control relevant system identification using orthonormal basis filters |
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Control relevant system identification deals with developing a dynamic model that can be used for design of a controller from experimental data. In this paper an iterative technique based on orthonormal basis filters is used to develop reduced complexity, control relevant models from input-output data that is corrupted with noise. It is also shown that a parsimonious general orthonormal basis filter (GOBF) model can be developed from a crude estimate of time constant with no prior knowledge of time delay. Unlike ARX, ARMAX and similar techniques the method presented does not require prior knowledge of the time delay. The identification technique is tested using simulated data and the result is found to be sufficiently accurate. ©2007 IEEE.
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format |
Conference or Workshop Item |
author |
Tufa , L.D. Ramasamy , Marappagounder Shuhaimi , M. Patwardhan , S.C. |
author_facet |
Tufa , L.D. Ramasamy , Marappagounder Shuhaimi , M. Patwardhan , S.C. |
author_sort |
Tufa , L.D. |
title |
Control relevant system identification using orthonormal basis filters
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title_short |
Control relevant system identification using orthonormal basis filters
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title_full |
Control relevant system identification using orthonormal basis filters
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title_fullStr |
Control relevant system identification using orthonormal basis filters
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Control relevant system identification using orthonormal basis filters
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control relevant system identification using orthonormal basis filters |
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2007 |
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http://eprints.utp.edu.my/573/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-57949098588&partnerID=40&md5=854e2d34fdc31225c62006a63600f2f2 http://eprints.utp.edu.my/573/ |
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