A fast nonlinear model identification method
The identification of nonlinear dynamic systems using linear-in-the-parameters models is studied. A fast recursive algorithm (FRA) is proposed to select both the model structure and to estimate the model parameters. Unlike orthogonal least squares (OLS) method, FRA solves the least-squares problem r...
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| Veröffentlicht in: | IEEE transactions on automatic control 2005-08, Vol.50 (8), p.1211-1216 |
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| container_title | IEEE transactions on automatic control |
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| creator | Kang Li Jian-Xun Peng Irwin, G.W. |
| description | The identification of nonlinear dynamic systems using linear-in-the-parameters models is studied. A fast recursive algorithm (FRA) is proposed to select both the model structure and to estimate the model parameters. Unlike orthogonal least squares (OLS) method, FRA solves the least-squares problem recursively over the model order without requiring matrix decomposition. The computational complexity of both algorithms is analyzed, along with their numerical stability. The new method is shown to require much less computational effort and is also numerically more stable than OLS. |
| doi_str_mv | 10.1109/TAC.2005.852557 |
| format | Article |
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A fast recursive algorithm (FRA) is proposed to select both the model structure and to estimate the model parameters. Unlike orthogonal least squares (OLS) method, FRA solves the least-squares problem recursively over the model order without requiring matrix decomposition. The computational complexity of both algorithms is analyzed, along with their numerical stability. The new method is shown to require much less computational effort and is also numerically more stable than OLS.</description><identifier>ISSN: 0018-9286</identifier><identifier>EISSN: 1558-2523</identifier><identifier>DOI: 10.1109/TAC.2005.852557</identifier><identifier>CODEN: IETAA9</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Algorithm design and analysis ; Applied sciences ; Computational complexity ; Computer science; control theory; systems ; Control theory. 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Systems</subject><subject>Exact sciences and technology</subject><subject>fast recursive algorithm</subject><subject>Least squares methods</subject><subject>Matrix decomposition</subject><subject>Modelling and identification</subject><subject>Nonlinear dynamical systems</subject><subject>nonlinear system identification</subject><subject>Nonlinear systems</subject><subject>Numerical stability</subject><subject>Parameter estimation</subject><subject>System identification</subject><subject>US Department of Transportation</subject><issn>0018-9286</issn><issn>1558-2523</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqNkM1LAzEQxYMoWKtnD14WQU9um8_dybEUv6DgpZ5Dms1iyjapyfbgf2-WLRQ8eRqG-b3HvIfQLcEzQrCcrxfLGcVYzEBQIeozNCFCQEkFZedogjGBUlKoLtFVStu8VpyTCXpaFK1OfeGD75y3Oha70NiucI31vWud0b0LvtjZ_is01-ii1V2yN8c5RZ8vz-vlW7n6eH1fLlalYYD70lJmRG2Y4RUxBkvdaN0CoYJryTVtGm5l23BGsQYMbMPzu3xTY2aAb1jN2RQ9jr77GL4PNvVq55KxXae9DYekKBDGgIp_gDk2VIPj_R9wGw7R5xAKYPCqGGRoPkImhpSibdU-up2OP4pgNXSscsdq6FiNHWfFw9FWJ6O7NmpvXDrJKikFUJK5u5Fz1trTmUsqqpr9AmtAggE</recordid><startdate>20050801</startdate><enddate>20050801</enddate><creator>Kang Li</creator><creator>Jian-Xun Peng</creator><creator>Irwin, G.W.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Systems</topic><topic>Exact sciences and technology</topic><topic>fast recursive algorithm</topic><topic>Least squares methods</topic><topic>Matrix decomposition</topic><topic>Modelling and identification</topic><topic>Nonlinear dynamical systems</topic><topic>nonlinear system identification</topic><topic>Nonlinear systems</topic><topic>Numerical stability</topic><topic>Parameter estimation</topic><topic>System identification</topic><topic>US Department of Transportation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kang Li</creatorcontrib><creatorcontrib>Jian-Xun Peng</creatorcontrib><creatorcontrib>Irwin, G.W.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Aerospace Database</collection><jtitle>IEEE transactions on automatic control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kang Li</au><au>Jian-Xun Peng</au><au>Irwin, G.W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A fast nonlinear model identification method</atitle><jtitle>IEEE transactions on automatic control</jtitle><stitle>TAC</stitle><date>2005-08-01</date><risdate>2005</risdate><volume>50</volume><issue>8</issue><spage>1211</spage><epage>1216</epage><pages>1211-1216</pages><issn>0018-9286</issn><eissn>1558-2523</eissn><coden>IETAA9</coden><abstract>The identification of nonlinear dynamic systems using linear-in-the-parameters models is studied. 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| identifier | ISSN: 0018-9286 |
| ispartof | IEEE transactions on automatic control, 2005-08, Vol.50 (8), p.1211-1216 |
| issn | 0018-9286 1558-2523 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Algorithm design and analysis Applied sciences Computational complexity Computer science control theory systems Control theory. Systems Exact sciences and technology fast recursive algorithm Least squares methods Matrix decomposition Modelling and identification Nonlinear dynamical systems nonlinear system identification Nonlinear systems Numerical stability Parameter estimation System identification US Department of Transportation |
| title | A fast nonlinear model identification method |
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