Gradient-based iterative identification for MISO Wiener nonlinear systems: Application to a glutamate fermentation process

Abstract

This paper deals with modeling and parameter identification of multiple-input single-output Wiener nonlinear systems. The basic idea is to construct a multiple-input single-output Wiener nonlinear model and to derive the gradient-based iterative algorithm for the proposed model. The proposed method has been applied to identify the parameters of a glutamate fermentation process. The results of real data simulation show that this method is effective.