Journal of Applied Mathematics
Volume 2013 (2013), Article ID 565841, 6 pages
http://dx.doi.org/10.1155/2013/565841
Research Article

Least-Squares-Based Iterative Identification Algorithm for Wiener Nonlinear Systems

Lincheng Zhou,1 Xiangli Li,1,2 and Feng Pan1

1Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China
2Jiangsu College of Information Technology, Wuxi 214153, China

Received 28 December 2012; Accepted 26 April 2013

Academic Editor: Hui-Shen Shen

Copyright © 2013 Lincheng Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper focuses on the identification problem of Wiener nonlinear systems. The application of the key-term separation principle provides a simplified form of the estimated parameter model. To solve the identification problem of Wiener nonlinear systems with the unmeasurable variables in the information vector, the least-squares-based iterative algorithm is presented by replacing the unmeasurable variables in the information vector with their corresponding iterative estimates. The simulation results indicate that the proposed algorithm is effective.