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Identification methods for Wiener nonlinear systems based on the least squares and gradient iterations

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3 Author(s)
Dongqing Wang ; Coll. of Autom. Eng., Qingdao Univ., Qingdao, China ; Yanyun Chu ; Feng Ding

This paper derives a least squares based and a gradient based iterative identification algorithms for Wiener nonlinear systems. These methods separate one bilinear-parameter cost function into two linear-parameter cost functions, estimating directly the parameters of the Wiener systems. The simulation results confirm that the proposed two algorithms are valid and the least squares based iterative algorithm has faster convergence rates than the gradient based iterative algorithm.

Published in:

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Date of Conference:

15-18 Dec. 2009