Experimental Comparison of Methods for Multivariable Frequency Response Function Estimation
2007 (English)Report (Other academic)
Nonparametric estimation methods for the multivariable frequency response function are experimentally evaluated using closed-loop data from an industrial robot. Three classical estimators (H1, joint input-output, arithmetic mean) and two estimators based on nonlinear averaging techniques (harmonic mean, geometric/logarithmic mean) are considered. The estimators based on nonlinear averaging give the best results, followed by the arithmetic mean estimator, which gives a slightly larger bias. The joint input-output estimator, which is asymptotically unbiased in theory, turns out to give large bias errors for low frequencies. Finally, the H1 estimator gives the largest bias for all frequencies.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2007. , 18 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2827
System identification, Frequency response methods, Multivariable systems, Non-parametric identification, Closed-loop identification, Industrial robots
IdentifiersURN: urn:nbn:se:liu:diva-56149ISRN: LiTH-ISY-R-2827OAI: oai:DiVA.org:liu-56149DiVA: diva2:316949