Maximum Likelihood Identification of Wiener Models
2008 (English)In: Proceedings of the 17th IFAC World Congress, 2008, 2714-2719 p.Conference paper (Refereed)
The Wiener model is a block oriented model having a linear dynamicsystem followed by a static nonlinearity.The dominating approachto estimate the components of this model has been to minimize theerror between the simulated and the measured outputs. We show thatthis will in general lead to biased estimates if there is otherdisturbances present than measurement noise. The implications ofBussgangs theorem in this context are also discussed. For the casewith general disturbances we derive the Maximum Likelihood methodand show how it can be efficiently implemented. Comparisons betweenthis new algorithm and the traditional approach confirm that the newmethod is unbiased and also has superior accuracy.
Place, publisher, year, edition, pages
2008. 2714-2719 p.
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-89041DOI: 10.3182/20080706-5-KR-1001.00457ISBN: 978-3-902661-00-5OAI: oai:DiVA.org:liu-89041DiVA: diva2:606884
17th IFAC World Congress, Seoul, South Korea, July, 2008