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

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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.

Keywords

System modeling
Parameter estimation
Wiener nonlinear systems
Multiple-input single-output system
Gradient-based iteration
Glutamate fermentation process

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This work was supported by the National Natural Science Foundation of China (No. 61273131), the University Graduate Scientific Research Innovation Program of Jiangsu Province (CXLX12_0722), the Ph.D. Candidate Scientific Research Foundation of Jiangnan University (JUDCF11042), the 111 Project (B12018) and PAPD of Jiangsu Higher Education Institutions.

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