Revisiting Hammerstein system identification through the Two-Stage Algorithm for bilinear parameter estimation

Revisiting Hammerstein system identification through the Two-Stage Algorithm for bilinear parameter estimation
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通过双线性参数估计的两阶段算法重新审视 Hammerstein 系统辨识

DOI:
10.1016/j.automatica.2009.07.033
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发表时间:
2009-11
期刊:
影响因子:
6.4
通讯作者:
ong
ong
中科院分区:
计算机科学2区
文献类型:
--
作者:
Zhang, Qinghua;Ljung, Lennart;Wang, Ji;ong

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两阶段算法(TSA)已被广泛使用,并适用于Hammerstein系统的识别。它基本上是基于一个特定的制定Hammerstein系统的形式双线性参数化线性回归。本文的动机是一个有点矛盾的事实:虽然1998年Bai只在一些特殊的加权矩阵的情况下建立了TSA的最优性,但实际上通常使用未加权的TSA。本文证明了未加权TSA确实给出了用特定加权矩阵表示的加权非线性最小二乘问题的最优解。这提供了一个理论上的理由,未加权TSA,也导致了所获得的结果的推广的情况下,有色噪声与噪声白化。Hammerstein系统辨识的数值例子验证了理论分析。
The Two-Stage Algorithm (TSA) has been extensively used and adapted for the identification of Hammerstein systems. It is essentially based on a particular formulation of Hammerstein systems in the form of bilinearly parameterized linear regressions. This paper has been motivated by a somewhat contradictory fact: though the optimality of the TSA has been established by Bai in 1998 only in the case of some special weighting matrices, the unweighted TSA is usually used in practice. It is shown in this paper that the unweighted TSA indeed gives the optimal solution of the weighted nonlinear least squares problem formulated with a particular weighting matrix. This provides a theoretical justification of the unweighted TSA, and also leads to a generalization of the obtained result to the case of colored noise with noise whitening. Numerical examples of identification of Hammerstein systems are presented to validate the theoretical analysis.
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