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Mathematical Problems in Engineering
Volume 2013, Article ID 240929, 8 pages
Research Article

Recursive Least-Squares Estimation for Hammerstein Nonlinear Systems with Nonuniform Sampling

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
3School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
4Institute of Technology, University of Washington, Tacoma, WA 98402-3100, USA

Received 17 June 2013; Accepted 2 September 2013

Academic Editor: Victoria Vampa

Copyright © 2013 Xiangli Li 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.


This paper focuses on the identification problem of Hammerstein nonlinear systems with nonuniform sampling. Using the key-term separation principle, we present a discrete identification model with nonuniform sampling input and output data based on the frame period. To estimate parameters of the presented model, an auxiliary model-based recursive least-squares algorithm is derived by replacing the unmeasurable variables in the information vector with their corresponding recursive estimates. The simulation results show the effectiveness of the proposed algorithm.