Stochastic approximation in nonparametric identification of Hammerstein systems

被引：76

作者：

Greblicki, W ^{[1
]}

机构：

[1] Wroclaw Univ Technol, Inst Engn Cybernet, PL-50370 Wroclaw, Poland

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2002年 / 47卷 / 11期

关键词：

Hammerstein system; nonparametric identification; nonparametric regression; recursive identification; stochastic approximation; system identification;

D O I：

10.1109/TAC.2002.804483

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：

Derived from the idea of stochastic approximation, recursive algorithms to identify a Hammerstein system are presented. Two of them recover the characteristic of the nonlinear memoryless subsystem, while the third one estimates the impulse response of the linear dynamic part. The apriori information about both subsystems is nonparametric. Consistency in quadratic mean is shown, and the convergence rate is examined. Results of numerical simulation are also presented.

引用

页码：1800 / 1810

页数：11

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