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Estimation of generalised Hammerstein-Wiener systems

By Adrian Wills and Brett Ninness


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

Topics: gradient-based search, output-error, Hammerstein, Wiener, black-box
Publisher: International Federation of Automatic Control (IFAC)
Year: 2009
DOI identifier: 10.3182/20090706-3-FR-2004.00183
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