Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1703609 | Applied Mathematical Modelling | 2013 | 7 Pages |
Abstract
This paper focuses on the identification problem of Wiener nonlinear output error systems. The application of the key-term decomposition technique provides a special form of the Wiener model with polynomials, where all the model parameters to be estimated are separated. To solve the identification problem of Wiener nonlinear output error systems with the unmeasurable variables in the information vector, an auxiliary model-based gradient iterative algorithm is presented by replacing the unmeasurable variables with their corresponding iterative estimates. The performances of the proposed algorithm are analyzed and compared by using numerical examples.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Lincheng Zhou, Xiangli Li, Feng Pan,