On the Detection of Nonlinearities in Sampled Data
2012 (English)In: Proceedings of the 16th IFAC Symposium on System Identification, 2012, 1587-1592 p.Conference paper (Refereed)
Here we deal with the choice of the sampling rate in nonlinear system identification applications. In particular, we focus on the effect of the sampling rate when the prediction-error method is used. On one hand, a high sampling rate is advantageous since it enables the measurement of high-frequent nonlinear components in the output signal of the system without aliasing. However, a high sampling rate might also make it harder to realize that the system is nonlinear, since the nonlinearities cannot be detected in the residuals from a linear model in some cases. Here, this phenomenon is illustrated in a couple of numerical examples and a way to avoid it is proposed.
Place, publisher, year, edition, pages
2012. 1587-1592 p.
, IFAC-PapersOnLine, ISSN 2405-8963 ; 45(16)
Nonlinear system identification, Identification for control
IdentifiersURN: urn:nbn:se:liu:diva-93278DOI: 10.3182/20120711-3-BE-2027.00307ISBN: 978-3-902823-06-9OAI: oai:DiVA.org:liu-93278DiVA: diva2:623899
16th IFAC Symposium on System Identification, Brussels, Belgium, 11-13 July, 2012