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Mathematical Problems in Engineering
Volume 2015, Article ID 125868, 7 pages
Research Article

Twin Support Vector Machine Method for Identification of Wiener Models

King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia

Received 7 January 2015; Revised 11 April 2015; Accepted 16 April 2015

Academic Editor: Shiliang Sun

Copyright © 2015 Mujahed Al-Dhaifallah. 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.


Twin support vector regression is applied to identify nonlinear Wiener system, consisting of a linear dynamic block in series with static nonlinearity. The linear block is expanded in terms of basis functions, such as Laguerre or Kautz filters, and the static nonlinear block is determined using twin support vector machine regression. Simulation of a control valve model and pH neutralization process have been presented to show the features of the proposed algorithm over support vector machine based algorithm.