Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/919667
- Title
- Estimation of generalised Hammerstein-Wiener systems
- Author/Creator
-
Wills, Adrian;
Ninness, Brett
- Institution
- The University of Newcastle. Faculty of Engineering & Built Environment, School of Electrical Engineering and Computer Science
- 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.
- 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
- Date
- 2009
- Publisher
- International Federation of Automatic Control (IFAC)
- Keyword(s)
-
gradient-based search;
output-error;
Hammerstein;
Wiener;
black-box
- Resource Type
- conference paper
- Identifier
- http://hdl.handle.net/1959.13/919667
- Identifier
- ISBN:9783902661470
- Identifier
- ISSN:1474-6670
- Reviewed

33 Visitors
34 Hits
0 Downloads