Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
711170 | IFAC-PapersOnLine | 2015 | 6 Pages |
Abstract
The paper reports a method for identification of parametric models that are linear and time-invariant in parameters, but arbitrarily nonlinear in signals. Set-bounding solutions are exploited to simultaneously identify and parametrize the model structure. Measures of set-solution quality are used as fitness measures in evolving the structure. Experiments verify effective NARX and NARMAX identification in complex unmodeled disturbances.
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