Frequency Domain System Identification Toolbox for Matlab: Characterizing Nonlinear Errors of Linear Models

System identification often means the determination of linear models from input-output data. The behaviour of many systems can be described by an s-domain or z-domain transfer function model, at least for a given excitation amplitude range. The quality of the fit can be assessed by the analysis of the residuals, that is, of the difference between the measured data and the model. However, even slight nonlinearities can be misleading, by causing part of the residuals non-explicable by the linear model. We cannot simply tell if the excess residual error is due to undermodelling or to nonlinear system behaviour. This can 14th IFAC Symposium on System Identification, Newcastle, Australia, 2006 lead to erroneous overmodelling. Therefore, characterisation of the nonlinear system behaviour is essential in the verification of line The Frequency Domain System Identification To analysis tools of nonlinear system behaviour. Speci allow the description of nonlinearity levels. By th possible even if nonlinear error terms excess line 2006 IFAC