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SUMMARY:Nonparametric preprocessing in system identification: a powerful t
 ool.
DTSTART:20101105T101500
DTSTAMP:20260504T181119Z
UID:312675333097224683489c72867ed76fa00477703cfe4e131e9a6090
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. J. Schoukens\, Dept. of Fundamental Electricity and Inst
 rumentation\, Vrije Universiteit Brussel\, Belgium \nMy dream is to develo
 p robust identification methods that provide good models to the user witho
 ut requesting advanced user interactions. High quality nonparametric frequ
 ency response function measurements together with nonparametric measuremen
 ts of the disturbing noise power spectra turn out to be important steps to
  make this dream comes through. Nonparametric models can not only be used 
 to initialize more advanced identification methods\, the results can also 
 be used directly in modern control design approaches.\n \nIn this presenta
 tion we study first the properties of the existing nonparametric methods f
 or estimating the plant and noise transfer functions of a linear dynamic s
 ystem. The analysis is based on the recent insight that leakage errors in 
 the frequency domain have a smooth nature that is completely similar to th
 e initial transients in the time domain. This not only allows us to unders
 tand better the existing classic methods\, but also opens the road to new 
 better performing algorithms. These will be presented in the second part o
 f the presentation. The presentation includes the output error setup\, the
  errors-in-variables setup\, and measurements under feedback conditions. E
 ventually\, some of the methods are illustrated on experimental data. 
LOCATION:ME C2405
STATUS:CONFIRMED
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