Estimation of generalised Hammerstein-Wiener systems

Title: Estimation of generalised Hammerstein-Wiener systems
Creator: Wills, Adrian; Ninness, Brett
Relation: 15th IFAC Symposium on System Identification (SYSID 2009). Proceedings of the 15th IFAC Symposium on System Identification (Saint-Malo, France 6-8 July, 2009) p. 1104-1109
Publisher Link: http://dx.doi.org/10.3182/20090706-3-FR-2004.00183
Publisher: International Federation of Automatic Control (IFAC)
Resource Type: conference paper
Date: 2009
Description: This paper examines the use of a so-called "generalised Hammerstein-Wiener" model structure that is formed as the concatenation of an arbitrary number of Hammerstein systems. The latter are taken here to be memoryless non-linearities followed by linear time invariant dynamics. Hammerstein, Wiener, Hammerstein-Wiener and Wiener-Hammerstein models are all special cases of this structure. The parameter estimation of this model is investigated by using a standard prediction error criterion coupled with a robust gradient based search algorithm. This approach is profiled using the Wiener-Hammerstein system benchmark data, which illustrates it to be effective and, via Monte-Carlo simulation, relatively robust against capture in local minima.
Subject: gradient-based search; output-error; Hammerstein; Wiener; black-box
Identifier: http://hdl.handle.net/1959.13/919667
Identifier: uon:8947
Identifier: ISBN:9783902661470
Identifier: ISSN:1474-6670
Language: eng
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