Identification of nonlinear dynamic systems described by Hammerstein state-space models with discontinuous nonlinearities

被引：0
作者：
Salhi H. [1 ]
Kamoun S. [1 ]
机构：
[1] Laboratory of Sciences and Technique of Automatic Control and Computer Engineering (Lab-SAT), National Engineering School of Sfax (ENIS), University of Sfax, Sfax
来源：
International Journal of Engineering Systems Modelling and Simulation | 2017年 / 9卷 / 03期
关键词：
adjustable model; dead zone nonlinearity; discontinuous nonlinearities; Hammerstein model; Kalman filter; least squares technique; parameter estimation; preaload; recursive algorithm; state estimation;
D O I：
10.1504/IJESMS.2017.085059
中图分类号：
学科分类号：
摘要：
This paper deals with the parameter estimation problem of Hammerstein state-space models with different nonlinearities. The basic idea is to develop a recursive algorithm which estimate jointly the system model parameters and the state variables by combining the adjustable model method, the least squares technique and the Kalman filter. A numerical example is provided to test the flexibility and the effectiveness of the proposed algorithm. Copyright © 2017 Inderscience Enterprises Ltd.
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页码：127 / 135
页数：8
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