An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems

被引:446
作者
Bai, EW [1 ]
机构
[1] Univ Iowa, Dept Elect & Comp Engn, Iowa City, IA 52242 USA
基金
美国国家科学基金会;
关键词
bilinear systems; system identification; parameters estimation; nonlinear models; modelling;
D O I
10.1016/S0005-1098(97)00198-2
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 [计算机科学与技术];
摘要
An optimal two-stage identification algorithm is presented for Hammerstein-Wiener systems where two static nonlinear elements surround a linear block. The proposed algorithm consists of two steps: The first one is the recursive least squares and the second one is the singular value decomposition of two matrices whose dimensions are fixed and do not increase as the number of the data point increases. Moreover, the algorithm is shown to be convergent in the absence of noise and convergent with probability one in the presence of white noise. (C) 1998 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:333 / 338
页数:6
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