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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| Published in: | IEEE transactions on automatic control Vol. 50; no. 8; pp. 1211 - 1216 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York, NY
IEEE
01.08.2005
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 0018-9286, 1558-2523 |
| Online Access: | Get full text |
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| Summary: | 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. |
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| Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 content type line 23 |
| ISSN: | 0018-9286 1558-2523 |
| DOI: | 10.1109/TAC.2005.852557 |