Abstract
A modeling method for nonlinear MIMO systems is introduced ‘breeding’ the best capabilities of the classical Wiener representation and NN-type models. The original Wiener representation consists of linear dynamics (Laguerre filters) and static nonlinear mapping (polynomial expansion). In Wiener-NN, static nonlinear mapping is approximated with NN. The feedforward Wiener-NN is suitable for modeling of finite settling time systems. The Wiener-NN with feedback can also be used for modeling of autonomous type systems. MLP has been used as NN. The Extended Kalman filter is used in the recursive estimation of the parameters of NOE Wiener-MLP with feedback. Biotechnical processes and chromatographic separation process are used as modeling cases.
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