Regressor and structure selection in NARX models using a structured ANOVA approach

Authors:
Ingela Lind;Lennart Ljung
Affiliations:
Division of Automatic Control, Department of Electrical Engineering, Linköpings Universitet, SE-58337 Linköping, Sweden;Division of Automatic Control, Department of Electrical Engineering, Linköpings Universitet, SE-58337 Linköping, Sweden
Venue:
Automatica (Journal of IFAC)
Year:
2008

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Abstract

Regressor selection can be viewed as the first step in the system identification process. The benefits of finding good regressors before estimating complex models are especially clear for nonlinear systems, where the class of possible models is huge. In this article, a structured way of using the tool analysis of variance (ANOVA) is presented and used for NARX model (nonlinear autoregressive model with exogenous input) identification with many candidate regressors.