Considering the measurement noise for a nonlinear system identification with evolutionary algorithms


This paper deals with the identification of a nonlinear system modelled by a nonlinear output error (NOE) model when the system output is disturbed by an additive zero-mean white Gaussian noise. In that case, standard on-line or off-line least squares methods may lead to poor results. Here, our approach is based on evolutionary algorithms. Although their… (More)


4 Figures and Tables