Identification of a nonlinear full-vehicle model for semi-active damper controller synthesis

ABSTRACT: The focus of this paper is the identification of a nonlinear full vehicle model. The identification task is realized as a weighted nonlinear least squares optimization problem, which minimizes the 2-norm of the errors between the power spectral density (PSD) of the measured sensor signals and that of the simulated sensor signals. Subsequently the parameterized vehicle model is reduced to a quarter vehicle model. This model is then utilized during the synthesis of an LPV controller employing semi-active dampers.